Background: Bone fracture fixation surgery is one of the most commonly performed surgical procedures in the orthopedic field. However, fracture healing complications occur frequently, and the choice of the most optimal surgical approach often remains challenging. In the last years, computational tools have been developed with the aim to assist preoperative planning procedures of bone fracture fixation surgery.Objectives: The aims of this review are 1) to provide a comprehensive overview of the state-of-the-art in computer-assisted preoperative planning of bone fracture fixation surgery, 2) to assess the clinical feasibility of the existing virtual planning approaches, and 3) to assess their clinical efficacy in terms of clinical outcomes as compared to conventional planning methods.Methods: A literature search was performed in the MEDLINE-PubMed, Ovid-EMBASE, Ovid-EMCARE, Web of Science, and Cochrane libraries to identify articles reporting on the clinical use of computer-assisted preoperative planning of bone fracture fixation.Results: 79 articles were included to provide an overview of the state-of-the art in virtual planning. While patient-specific geometrical model construction, virtual bone fracture reduction, and virtual fixation planning are routinely applied in virtual planning, biomechanical analysis is rarely included in the planning framework. 21 of the included studies were used to assess the feasibility and efficacy of computer-assisted planning methods. The reported total mean planning duration ranged from 22 to 258 min in different studies. Computer-assisted planning resulted in reduced operation time (Standardized Mean Difference (SMD): -2.19; 95% Confidence Interval (CI): -2.87, -1.50), less blood loss , decreased frequency of fluoroscopy , shortened fracture healing times  and less postoperative complications (Risk Ratio (RR): 0.64, 95% CI: 0.46, 0.90). No significant differences were found in hospitalization duration. Some studies reported improvements in reduction quality and functional outcomes but these results were not pooled for meta-analysis, since the reported outcome measures were too heterogeneous.Conclusion: Current computer-assisted planning approaches are feasible to be used in clinical practice and have been shown to improve clinical outcomes. Including biomechanical analysis into the framework has the potential to further improve clinical outcome. Bone fractures are the most common form of hospitalized trauma and result in a significant healthcare burden. A systematic analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 has estimated the global number of new fractures to be 178 million . Since fSurgical treatment of bone fractures aims to restore the original anatomy of the bone in order to recover the lost motor function and is one of the most frequent surgical procedures in the orthopaedic field . The surThere are typically many options for fracture fixation and the optimal fixation is highly dependent on the bone geometry and fracture pattern. Therefore, the surgical treatment of bone fractures calls for detailed preoperative planning. Conventionally, the planning of bone fracture fixation surgery is done using plain radiographs, tracing paper, and view boxes . The sur1) Increased understanding of the fracture characteristics such as the direction of the fracture lines, size of the fracture, and the number and location of fragments .2) Avoid extensive dissection and soft tissue stripping, repeated manipulations of reduction fixation, possibly leading to shorter operation time and less bleeding .., appropriate choice of screw lengths and plate sizes (3) Choose optimal operative approach, e.gte sizes .4) Automatic contouring or pre-bending of fixation devices and design of drilling guides .5) Practice surgery virtually and decrease learning curve for surgeons .6) Better doctor-patient communication about preoperative plan .Computer-assisted preoperative planning (CAPP), or virtual surgical planning (VSP), may resolve many of these issues associated with conventional planning. In the field of fracture fixation surgery, VSP usually includes: 1) obtaining a three-dimensional (3D) anatomic reconstruction of the fractured bone, 2) virtual bone fragment reduction, and 3) virtual fixation of the fragments using implants . PossiblVSP is increasingly available to orthopedic surgeons  and is rDespite existing reservations, many studies suggest that VSP of bone fracture fixation is feasible to be employed in clinical practice and it improves clinical outcomes. However, the clinical efficacy and feasibility of existing VSP systems for bone fracture fixation have never been systematically reviewed. Previous reviews have focused on the description and technical details of the involved steps  or on a The aim of this review is to assess the clinical applicability of computer-assisted preoperative planning of bone fracture fixation surgery. This will be done by 1) providing a comprehensive overview of the state-of-the-art approaches including existing software systems and design gaps, 2) assessing the clinical feasibility of the existing approaches, and 3) assessing the clinical efficacy of the existing approaches in terms of clinical outcomes as compared to conventional planning methods.The clinical feasibility will be assessed in terms of the required input data, segmentation methods and duration, virtual fracture reduction methods and duration, and virtual fracture fixation methods and duration. The assessed clinical outcomes will include differences in operation time, blood loss, fluoroscopy frequency, reduction quality, functional outcomes, postoperative complications, and fracture healing time between computer-assisted and conventional planning.This paper is organized as follows. First, the literature search strategy and results are presented in The literature search was performed according to the Preferred Reporting Items for Systematic Reviews (PRISMA) . This meThe MEDLINE-PubMed, Ovid-EMBASE, Ovid-EMCARE, Web of Science, and Cochrane libraries were searched on March 3rd of 2022 without a limit on the publication date. The search strategy was developed in collaboration with an experienced medical librarian. It was developed to identify studies related to computer-assisted preoperative planning of bone fracture fixation. These aspects, including different ways to describe the aspect, were combined to construct the used search strings. 1) were not clinically applied1) Animal studies2) Cadaver studies3) Retrospective simulation studies2) did not focus on bone fracture fixation1) Deformity corrections2) Arthroplasties3) Spinal fusion4) Orbital floor reconstructions3) did not use a virtual model 4) did not focus on preoperative planning1) Only intra-operative navigation2) Studies about the classification of injuries by means of computer modelsTo provide a comprehensive overview of the state-of-the-art in computer-assisted preoperative planning of bone fracture fixation, studies were only included if they reported on clinically applied virtual planning of bone fracture fixation. This means that studies were excluded if they:Additionally, studies that were not available in English were excluded.To analyze the efficacy and feasibility of existing software approaches, additional inclusion criteria were formulated. Studies were included for this analysis if they had a control group and reported on 1) simulation times and/or 2) clinical outcomes.General study characteristics, investigated systems, fracture classification and intervention, input data, segmentation methods and duration, virtual reduction methods and duration, virtual fixation methods and duration, analysis methods and duration, clinical outcome measures, and main conclusions were extracted for the included studies with a control group. Studies without a control group were only screened for the investigated system and fracture type to get an overview of the existing systems.Analysis of the extracted clinical outcomes  was performed in Review Manager (version 5.4.1). Continuous variables such as operation times, the amount of blood loss, fluoroscopy frequency, fracture healing time and duration of hospitalization are presented as means plus standard deviations. Standardized mean differences (SMD/Cohen’s d) were computed, since the scales of the reported outcomes are considerably different. A random effects model was used since the studies have been conducted under dissimilar conditions and for different fracture types. The postoperative complication rates are presented as frequencies and risk ratios (RR) were computed, i.e., the ratio of the complication probability in the VSP group to the probability in the conventional group.The search yielded a total of 1,007 studies, and after the removal of duplicates, 523 studies were screened based on title and abstract for eligibility. Based on this, 319 studies were excluded, and the remaining 204 records were sought for retrieval. 10 records were not retrieved or were not available in English. Consequently, 194 reports were assessed for eligibility based on full-text screening. 115 records were excluded based on the exclusion criteria outlined in Computer-assisted preoperative planning of bone fracture fixation typically consists of the following stages: 1) generation of patient-specific geometrical models, 2) virtual bone fracture reduction, 3) virtual bone fracture fixation, and 4) analysis of surgical planning. To make sure the surgery is done according to planning, 5) intra-operative guidance may be provided. Alternatively, 3D printed models are sometimes used as well for some stages of the planning. Each of these stages is detailed in the following sections. An overview of the stages is given in The first step in VSP is the construction of a 3D patient-specific model that represents the bone and bone fragments involved in the fracture. In general, these geometrical models can be made using two main approaches:The first approach–which is, according to the authors’ knowledge, the only one currently used in clinical practice—requires the application of 3D medical imaging technologies, such as computed tomography (CT). The second approach is to use statistical shape models (SSMs), which provide a way to generate an average bone model including the main modes of variation of a given population . These tAfter image acquisition using 3D medical imaging technologies . AdditioAfter 3D reconstruction, the bone model typically needs post-processing to separate the fracture fragments. This fragmentation is especially challenging in comminuted fractures where fragments might overlap. Typically, the separation is already integrated in the segmentation procedure, by manually editing the used segmentation masks in the 2D slices . In otheCurrently, this stage of the planning requires a high amount of time, manual user interaction and sometimes, expert knowledge. All of the commercially available VSP software rely on this approach using segmentation of medical CT images . In SectAn alternative approach for the creation of 3D geometrical models is to use SSMs or atlases of bones. A personalized model of the given patient can then be created using either 1) parametric functions to correlate patient-specific characteristics to certain modes of variations or 2) using two-dimensional (2D) imaging modalities.These patient-specific characteristics can be either simple morphometric parameters that can be read from X-ray radiographs   or otherIt has also been proposed to use 2D imaging modalities and 2D to 3D atlas-based registration methods to reconstruct a 3D model based on two orthogonal 2D radiographic images. After the construction of a 3D geometrical model of the fractured bone, virtual bone fracture reduction is typically performed. This is the process by which the bone fragments are rotated and translated to recover their original anatomical position. There are different methods to achieve this virtual reduction. The most common method is by free-hand reduction of the bone fragments using manual translation and rotation through computer mouse interaction . The comIt is also possible to manually reduce the bone fragments using more advanced interfaces such as haptic systems or virtual reality (VR) environments . This haMany automated reduction methods have also been proposed and tested in experimental settings only. The first class of methods relies on the incorporation of the mirrored healthy contralateral bone to facilitate reduction. The in-house developed software CASPA  was used by This mirroring method relies on the assumption that the contralateral bones are symmetric, which is often not true in case of natural shape differences or bilateral trauma . TherefoThe last automated virtual reduction method is based on the matching of the fracture lines of the different fragments. Many authors have attempted to apply this method but often struggle with challenging fracture line definitions. inter aliaIt is also possible to directly use the mirrored contralateral healthy bone or an SSM template for the design of patient-specific implants, leaving out the virtual fracture reduction step. This has been done by After virtual fracture reduction, the next phase is typically to virtually place a fixation device to stabilize the fracture. There are different approaches to do this. The implants can either be chosen from a library of existing implants , 2019 anSome authors also suggest a semi-automated implant or trajectory design, even though this is currently only done in experimental studies. The patient-specific implants that are used for virtual fixation are usually not readily available. In these cases, it is possible to either 3D print the designed implants or to pre-contour existing implants on a 3D printed reduced bone model. One study by Using conventional methods, osteosynthesis plates used for the fixation of fractures often require multiple intraoperative contouring maneuvers to fit the individual adequately . This reIn some studies, the quality of the planned reduction and fixation is analyzed. Typically, only the geometrical quality is analyzed. This might include an evaluation of the achieved reduction, the fit of the implant and the screw trajectories, either qualitatively or quantitatively. Only very few systems evaluate the biomechanical quality of the chosen fixation approach. Since the bone healing response and outcome is highly dependent on the biomechanical environment within the fracture , this isTheoretically, it is also possible to simulate the patient-specific healing response following a certain fixation scheme. By coupling the mechanical signals outputted by the FEA to changes in biological parameters using partial differential equations or agent-based models, the bone regeneration process can be simulated . HoweverAfter VSP, it is possible to use aiding techniques to guide the surgery according to the planning. This is termed intra-operative navigation and can be conducted by means of image fusion with intra-operative fluoroscopy. However, this is outside the scope of this review and has already been extensively reviewed by other authors including Patient-specific instrumentation (PSI) such as CAD drilling guides, CAD implants or pre-contoured implants may also be used to make sure the surgery is performed according to the preoperative planning. Using patient-specific or pre-contoured implants, it can be ensured that the planned reduction is achieved, since the implants are designed in such a way that they optimally fit the reduced bone. An alternative is to use patient-specific drilling guides to translate the planned screw trajectories towards the actual surgery. It has been shown that this permits more accurate and efficient reductions compared with the freehand technique .The 79 studies included in this review were screened for the used software solution. An overview of these systems is given in Of the 21 included studies that compare conventional planning with computer-assisted planning, the study characteristics, investigated VSP systems, fracture classification and used VSP approaches are summarized in In 16 studies reported on operation time . All stu15 studies reported on intra-operative blood loss  and all All studies that investigated fluoroscopy frequency  found thp > 0.05). Because no clear indications were given that a normal distribution could be assumed, the results were excluded from the meta-analysis, which required means and standard deviations as input. Out of the other three studies, only Four studies investigated fracture healing time differences between the VSP and conventional planning groups . Howeverp < 0.05) using a Mann-Whitney test or the Kruskal–Wallis test (not specified) but this result was not reproduced by the meta-analysis in this review, which uses a t-test  construction of patient-specific geometrical models, 2) virtual bone fracture reduction, 3) virtual bone fracture fixation, 4) analysis of the fixation reduction and/or fixation, and 5) intra-operative navigation. The first three stages are already routinely applied in clinical practice, the fourth stage rarely, and the fifth stage is outside the scope of this review.Construction of patient-specific geometrical models (stage 1) currently relies on 3D imaging technologies, more specifically on thin-slice CT scans. The segmentation of the bone fragments from the CT scans is usually done using semi-automatic approaches, often relying on intensity thresholding, region growing techniques and manual adjustments. The mean duration of the segmentation ranged from 6.89 to 83 min in the different studies. Many studies are currently focused on automatizing the segmentation of bone, and with the further development of machine learning for these purposes, efficient segmentation methods will hopefully continue to improve . HoweverVirtual bone fracture reduction (stage 2) currently usually relies on manual rotation and translation of the bone fragments using mouse interaction. Some studies employed a semi-automatic approach, requiring manual selection of points on each fragment and subsequent automatized reduction of the fragments. The mean time required for virtual reduction ranged from 5 to 23 min in the different studies. However, many experimental systems are currently investigating more automatized reduction methods with promising results.Implants used for virtual bone fracture fixation (stage 3) are usually either chosen from an implant database and scaled or designed for the specific patient using CAD tools. The mean reported times required for (design and) implantation of the fixation device range from 10 to 73.23 min in the different studies.Analysis of the planned surgery (stage 4) is currently rarely done and when done, it mainly relies on a geometrical evaluation , ignorinAnother aspect to consider regarding the existing VSP approaches is the fact that soft tissues are usually not considered  was chosen as an outcome measure in the meta-analysis, but this outcome measure is harder to interpret. Thirdly, potential bias due to differences in skill levels of the surgeons could exist and it is unclear whether the demonstrated benefits will also easily translate to other surgeons. As an example, Chen et alAn alternative to virtual surgical planning is the use of 3D printed hand-held fracture models. In conclusion, computer-assisted preoperative planning of bone fracture fixation surgery has been shown to be feasible to be employed in the clinical routine and to improve intra-operative efficiency in terms of operation time, blood loss, and fluoroscopy frequency. Additionally, using VSP yields shortened fracture healing times and less postoperative complications compared to conventional planning. Some studies have also reported improved reduction quality and functional outcomes. Moreover, VSP has the potential to provide biomechanical feedback on fracture stability, known to highly influence the healing outcome. Future efforts should focus on developing more efficient frameworks that also incorporate biomechanical analyses.


Impulsivity, as a multidimensional construct, has been linked to eating disorders (EDs) and may negatively impact treatment response. The study aimed to identify the dimensions of impulsivity predicting poor remission of ED symptoms. A total of 37 ED patients underwent a baseline assessment of impulsive personality traits and inhibitory control, including the Stroop task and the emotional go/no-go task with event-related potentials (ERPs) analysis. The remission of EDs symptomatology was evaluated after 3 months of cognitive-behavioral therapy (CBT) and at a 2-year follow-up. Poor remission after CBT was predicted by poor inhibitory control, as measured by the Stroop task. At 2 years, the risk of poor remission was higher in patients with higher novelty seeking, lower inhibitory control in the Stroop and in ERPs indices (N2 amplitudes) during the emotional go/no-go task. The present results highlight inhibitory control negatively impacting both short- and long-term symptomatology remission in ED patients. On the other hand, high novelty seeking and ERPs indices of poor inhibition seem to be more specifically related to long-term remission. Therefore, a comprehensive assessment of the impulsivity dimension in patients with ED is recommended to tailor treatments and improve their efficacy. Impulsivity is recognized as a multidimensional construct, reflecting multiple and separable psychological dimensions. An important contribution to this multidimensional conception has been provided by the UPPS model, which describes different personality traits that reflect impulsive behaviors .From a neuropsychological perspective, the cognitive functions linked to impulsivity include inhibitory control and decision-making processes . InhibitImpulsivity has been proposed as a transdiagnostic feature of eating disorders (EDs) ,8. From Impulsivity plays a role in the etiology and maintenance of ED symptoms, which may have important implications for therapy response. Cognitive-behavioral therapy (CBT) is one of the most common and effective treatments, which have been shown to reduce EDs symptoms . HoweverAlthough impulsivity is not necessarily dysfunctional in the nonclinical population , in indiRegarding inhibitory control, studies in patients with EDs have shown difficulties in both motor and cognitive inhibition ,27,28,29Previous studies showed the association between poor decision making and treatment outcome in EDs ,38. HoweThe present study aimed to analyze the impact of several facets of impulsivity in ED therapy response. Within this scope, multiple components of impulsivity were evaluated in a comprehensive perspective, including: (1) impulsive personality, measured by the UPPS dimensions and novelty seeking trait; (2) inhibitory control process, measuring cognitive inhibition with a Stroop task; and (3) motor inhibition, measured with an emotional go/no-go task with EEG recording.This multidimensional impulsivity assessment was conducted at baseline, and regression models were adopted to identify which dimensions predicted ED symptomatologic remission after CBT treatment and at a longer follow-up . We hypothesized that the most impulsive individuals would present partial or non-remission of EDs symptomatology, after CBT and at the longest follow-up. Different dimensions of impulsivity are expected to contribute to suboptimal remission of EDs symptoms, observed both immediately after treatment and in the medium term.n = 20) and bulimic spectrum disorders (BSD n = 17), including bulimia nervosa (BN) and binge eating disorder (BED), according to DSM-5 criteria [A total of 37 treatment-seeking individuals with ED were consecutively recruited at the ED Unit within the Department of Psychiatry at Bellvitge University Hospital (HUB)—a public health hospital certified as a tertiary care center with a highly specialized unit for the treatment of ED in Barcelona (Spain). To avoid the possible gender difference in impulsivity shown in the literature , recruitcriteria . PatientThe Temperament and Character Inventory-Revised (TCI-R)  validateThe UPPS-P Impulsivity Scale  is a 59-The Eating Disorders Inventory (EDI-2)  was adopThe Stroop Color–Word Test (SCWT)  is a papThe emotional go/no-go task  is a comThe electroencephalogram (EEG) was recorded continuously throughout the emotional go/no-go task using PyCorder (BrainVision). In total, 60 active Ag/AgCI electrodes were placed into an EEG recording cap (EASYCAP GmbH), distributed according to the 10–20 system; additional 3 electrodes were adopted for recording the vertical and horizontal electrooculogram (EOG), and Cz was used as an online reference. Impedances were kept below 20 kΩ using the SuperVisc high-viscosity electrolyte gel for active electrodes. Signals from all channels were digitized with a sampling rate of 500 Hz and 24 bit/channel resolution and online filtered between 0.1 and 100 Hz. Offline EEG analyses were performed with Brain Vision Analyser consisting of the following steps: high pass filtering at 0.1 Hz, low pass filtering at 30 Hz  and a notch filter at 50 Hz; raw data inspection for manual detection of artifacts and screening for bad channels, semi-automatic eye-blink correction using independent component analysis (ICA); artifact rejection of trials with an amplitude exceeding ±80 μV; EEG data were segmented into 1500 ms epochs from 500 ms before to 1000 ms after stimulus onset. Data were baseline corrected against the mean voltage during the 200 ms pre-stimulus periods. Artifact-free epochs were separately averaged for each subject in each experimental condition  and stimulus type . Event-related potentials (ERPs) analyses were based on visual inspection of the grand average waveforms and the existing literature. Peak amplitudes for the N2 were analyzed in a frontocentral electrodes cluster , in time windows between 200 and 380 ms. Since N2 is a negative peak wave, the more negative the values, the greater its amplitude.Patients received cognitive-behavioral therapy (CBT) at HUB, which was carried out by clinical psychology experts in the field. Patients diagnosed with AN completed a day hospital treatment program, which included group CBT sessions, lasting 90 min each, for 15 weeks. Treatment for the other EDs diagnoses  consisted of 16 weekly outpatient group sessions of CBT lasting 90 min. All patients attended follow-up sessions for a period of about two years’ duration. The goal of the treatment was to train patients to implement CBT strategies to reduce eating symptoms and to enable patients to acquire good healthy habits. Voluntary treatment discontinuation was categorized as dropout . Patients completing treatment were re-evaluated by their clinician to classify the remission of ED-related symptomatology. According to the DSM-5 criteria , full reStatistical analysis was carried out with Stata17 for Windows . The comp > 0.05 is indicative of adequate fit) [Two predictive models were obtained for the risk of poor treatment outcome  post-CBT and at 2-year follow-up, with logistic regression models adjusted for the ED subtype. The list of the potential predictors included the EEG measures registered during the emotional go/no-go task, the Stroop interference score and the impulsivity scores . Goodness of fit was assessed with the Hosmer–Lemeshow test (ate fit) , predictThe first block of The second block of At the 2-year follow-up, poor outcome was related to higher mean scores in the EDI-2 bulimia and impulse regulation scales, higher personality traits related to impulsivity , lower mean in the Stroop interference score and lower amplitude of the N2 wave in positive go trials, negative no-go trials and neutral go trials (mean differences with a significant result and/or effect size within at least the mild range). The ERPs and the topographical maps for the no-go negative condition are presented in The two logistic regression models displayed in The present study investigated the impact that impulsivity may have on therapy response in patients with EDs. Remission of ED symptomatology was evaluated after 3 months of CBT and at a 2-year follow-up. Multiple impulsivity dimensions were measured before treatment and significantly predicted poor treatment response, with more consistent evidence emerging at follow-up.With regard to impulsive personality traits, patients with poor remission following CBT were characterized by higher sensation seeking, whereas those with poor remission at follow-up were characterized by higher novelty seeking and higher UPPS total score. Novelty seeking emerged as a predictor of poor ED remission at follow-up, suggesting its relation to long-term remission of ED symptomatology. Along this line, some of the previous studies in patients with EDs showed associations between novelty seeking and a higher risk of dropout and suboptimal remission following CBT ,57.At a neurocognitive level, lower cognitive control predicted CBT outcome and remission at follow-up. Thus, individuals with difficulties in controlling the interference in the Stroop task showed poor remission of EDs after 3 months of CBT and at 2 years from treatment. In contrast, a study in patients with BED did not show an association between cognitive inhibition and reduction in ED psychopathology after treatment . The disRegarding motor inhibition, the lower amplitude of the N2 was associated with poor ED remission at follow-up. By contrast, the behavioral measures of response accuracy in the go/no-go task did not predict EDs remission, in line with some previous findings . It can Taken together, the present results highlighted the relevance of novelty seeking and inhibitory control in remission of EDs. A comprehensive assessment of impulsivity, including personality traits and neurocognitive indices of inhibitory control, may be particularly useful to improve treatment effectiveness. For instance, those individuals with a tendency to be more impulsive, excitable, dramatic and with intolerance to routine might benefit from treatment tailored to reduce their impulsive behaviors. To address the difficulties in inhibition, inhibitory control training with general or food-specific stimuli has been tested in individuals with EDs showing promising results ,64. ReceThe present findings should be considered under some limitations. First, the small sample was not suitable for the analysis of different ED subtypes, even though this variable was controlled for by statistical adjustment. Nevertheless, it could be of interest to study in the future the relationship between impulsivity dimensions and remission in specific ED subgroups. The small sample size also impacts the ability to avoid type II errors, the power capacity to detect the existence of a true relationship and the accuracy of the results obtained in the multivariate analyses. In this sense, the empirical evidence of this work should be interpreted with caution, pending future studies with larger samples to confirm or refute it. In addition, it should be considered that the assessment conducted in this study is difficult to perform in clinical samples, and therefore, research in this area is scarce and with low sample sizes. A second limitation is related to the nature of the outcome measure. Specifically, ED remission was assessed by the clinician at the end of treatment and at follow-up, according to the DSM-5 criteria. It is important to remark that optimal remission included only those individuals who fully remitted from symptomatology. Although this is particularly relevant in clinical practice, the adoption of a quantitative measure to track the changes in ED symptoms  should be considered in future works. Finally, the absence of a control group of patients undergoing treatment other than CBT or untreated individuals limits the interpretation and generalization of these results.Despite these limitations, several strengths of the study should be remarked on, such as the comprehensive assessment of impulsivity, which included personality, neuropsychological and neurophysiological measures. Thus, the multidimensional assessment enables a better characterization of impulsive profiles, which could interfere with treatment outcomes. Furthermore, remission of ED was not only considered immediately after treatment but also at a longer follow-up of 2 years, thus providing an opportunity to study the relationship between impulsivity and long-term recovery.In conclusion, high novelty seeking and low inhibitory control in individuals with EDs, but also specific neurophysiological indices, seem to contribute to poor remission of ED symptomatology. In particular, cognitive inhibition emerged as the dimension of impulsivity that more consistently predicted both short-term and medium-term remission of ED symptoms, confirming the importance of conducting a comprehensive assessment.From a clinical perspective, early detection of patients with a lack of inhibition is recommended to personalize treatments and improve their effectiveness. A replication of these results in individuals with different subtypes of EDs is needed in future studies assessing the response to treatment.


The U.S. Southeast has a high burden of SARS-CoV-2 infections and COVID-19 disease. We used public data sources and community engagement to prioritize county selections for a precision population health intervention to promote a SARS-CoV-2 testing intervention in rural Alabama during October 2020 and March 2021.We modeled factors associated with county-level SARS-CoV-2 percent positivity using covariates thought to associate with SARS-CoV-2 acquisition risk, disease severity, and risk mitigation practices. Descriptive epidemiologic data were presented to scientific and community advisory boards to prioritize counties for a testing intervention.In October 2020, SARS-CoV-2 percent positivity was not associated with any modeled factors. In March 2021, premature death rate , percent Black residents , preventable hospitalizations , and proportion of smokers  were associated with average SARS-CoV-2 percent positivity. We then ranked counties based on percent positivity, case fatality, case rates, and number of testing sites using individual variables and factor scores. Top ranking counties identified through factor analysis and univariate associations were provided to community partners who considered ongoing efforts and strength of community partnerships to promote testing to inform intervention.The dynamic nature of SARS-CoV-2 proved challenging for a modelling approach to inform a precision population health intervention at the county level. Epidemiological data allowed for engagement of community stakeholders implementing testing. As data sources and analytic capacities expand, engaging communities in data interpretation is vital to address diseases locally. From the outset of the global pandemic, the burden of COVID-19 disease has been dynamic across person, time, and space. In the months of the U.S. pandemic prior to vaccine availability, SARS-CoV-2 testing demand outweighed supply[Alabama is one of the lowest ranked states in many health metrics compared to the rest of the U.S. . Social In Alabama and similar settings, there is a need to optimize benefits of testing without exacerbating stigma and marginalization in underserved communities in order to control disease spread. We were funded to collaborate with academic institutions, local service organizations, and community health workers to promote SARS-CoV-2 testing in underserved communities in Alabama. We planned to use publicly available data on SARS-CoV-2, including risk mitigation practices and vulnerability to SARS-CoV-2 infection, to identify rural counties that would benefit most from community-based testing interventions.Here we describe how we used public data sources to explore strategies for identifying communities most at need for SARS-CoV-2 testing in two waves of selection during October 2020 and March 2021. We present our considerations and how our approach evolved with the pandemic, and lessons learned regarding the limitations of percent positivity in a state with inconsistent testing uptake to inform future work in other more rural settings with poorer public health infrastructure and healthcare.The Alabama Department of Public Health announced the first SARS-CoV-2 positive test result on March 13, 2020 . As of SFor reference, the U.S. census estimates that the nation’s population is approximately 76% White, 14% Black, with 89% high school graduates, and approximately 12% live in poverty .bamatracker.com[bamatracker.com[Data were downloaded periodically (approximately quarterly) from publicly available websites that collated and created visual representations of data reported by the Alabama Department of Public Health (ADPH). For the October 2020 county testing selections, data were downloaded from acker.com, a websiacker.com as well acker.com.We reviewed existing models summarizing, modeling, and predicting patterns in SARS-CoV-2 testing data provided by Johns Hopkins University, UniversPercent positivity, or the number of positive tests per 100 tests performed, has been widely used as a measure of SARS-CoV-2 disease burden since the beginning of the pandemic, providing insights into transmission within specific geographic areas. The CDCWe used linear regression models with dispersion with the primary outcome of average 14-day SARS-CoV-2 percent positivity summarized at the county level from October 2 – October 16, 2020. Model covariates included factors associated with risk of acquiring SARS-CoV-2  90-day average case fatality, case rate, and overall mortality rate by county. We identified the counties in the top quartile for percent positivity, case fatality, case rates, and mortality.In both rounds of selections, we also described race, 25, povFor both the October 2020 and March 2021 selections, the counties with the greatest COVID-19 burden as described above were shared with our Scientific and Community Advisory Boards to further hone selections and avoid overlapping outreach with other efforts  and to prioritize counties in need with known partners to promote community outreach efforts. Final selections were made by the Scientific and Community Advisory Boards in collaboration with the scientific leadership for this project.In October 2020, we modeled the predictors of past 14-day percent SARS-CoV-2 positivity and most recent county-level estimates for clinical factors, social determinants of health, and other measures of behavioral risk mitigation strategies we expected to inform testing and case rates. No covariates were significantly associated with county level percent positivity .In March 2021, we modeled predictors of average 7-day case positivity from 6/18/2020 – 3/31/2021 using similar covariates . In thisGiven the limited predictive power of the existing models and the models we built to identify counties with the greatest need, our county selections were determined based on descriptive epidemiology and input from scientific and community advisory boards. We described the counties in the top quartile for percent positivity, case fatality and case rates and below the median for number of testing sites and organized counties based on the number of parameters for which they were in the top quarter of the 67 counties in the state . Table 3Factor scores provided a ranking of counties with respect to 3 months SARS-CoV-2 positivity, case fatality rate, and SARS-CoV-2 testing sites/100k population. The factor rankings indicated in Priority counties selected in both phases of the project based on the descriptive epidemiology and mapped by the service areas of our community partners  who conducted the testing.Given the ongoing lack of discrimination between counties in the models we again used descriptive epidemiology and input from scientific and community advisory boards for the March 2021 selections. Here we present our approach to pragmatic identification of rural counties in need of a SARS-CoV-2 testing intervention in a Southern U.S. state at the peak of the 2019-first quarter 2021 phase of the U.S. SARS-CoV-2 epidemic. In order to select counties for rapid deployment of a testing intervention in a state with high testing need, we were tasked with quickly identifying priority counties using publicly-available data. Based on global and national guidance, we focused on SARS-CoV-2 percent positivity, 22. As In October 2020, no factors were associated with percent positivity in our models. This speaks to the fact that in these first waves of COVID-19 no population was immune, and testing was roughly similar across the counties, so it is not surprising that specific factors driving COVID transmission and positivity were not identified. In addition, more localized outbreaks and “super-spreader” events were randomly distributed in time and geographic area and therefore the time periods included in the models represent variable features of a dynamic epidemic. In March 2021, factors associated with increases in percent positivity were county level rates of premature death and prevIdentifying the appropriate metric to track in order to identify areas of testing demand during a rapidly evolving pandemic proved to be challenging. Case positivity was originally thought to be the best indicator of the next outbreak which would therefore inform aggressive testing strategies. This diThis team is led by HIV researchers who routinely wait years for public health data to be cleaned and available, in part due to the sensitive nature of HIV testing and related data , 45. TheIn recent years there has been a push for precision population health, leveraging big data to identify those at greatest risk to optimize delivery of the right intervention, to the right population, at the right time. Unlike diseases with more stable epidemiological and risk profiles, the dynamic nature of SARS-CoV-2, over geography and time, proved challenging for a model-based approach to inform precision population health tailored SARS-CoV-2 testing. A simplified approach based upon descriptive epidemiological data proved informative while allowing for meaningful engagement of essential community stakeholders and implementation partners ultimately charged with implementing testing in their local communities. As data sources and analytic capacities expand in scope and sophistication, leveraging traditional epidemiological data and analysis retains a vital role in engaging communities and building trust in data in order to optimally address communicable and non-communicable conditions in their local context.This is a methods paper to share lessons learned in selecting counties for a SARS-CoV-2 testing intervention but not an in-depth exploration of SARS-CoV-2 testing patterns and epidemiology in Alabama. The findings are unlikely to generalize to all settings and will be most applicable to other counties or states with strained public health systems in the U.S. healthcare context. Details regarding our testing intervention and findings are published elsewhere .We present a pragmatic approach to inform an evolving, pandemic community-level intervention. We also share lessons learned regarding the limits of test positivity in an outbreak where testing uptake is poor and where case positivity rates generally exceeded a threshold level to discern need in areas where nearly all counties had high need. Our current and future work highlights the importance of community partnerships, local knowledge to inform testing outreach and perhaps highlights the need for more centralized pandemic preparedness.


Glioblastoma sometimes develops with acute onset due to intracerebral hemorrhage. Although it is sometimes difficult to diagnose patients with hemorrhagic-onset glioblastoma at the acute phase of intracerebral hemorrhage (ICH), the progressive enlargement of perifocal edema or the development of contrast-enhanced lesion triggers the diagnosis of glioblastoma within six months. Herein, we present a rare case of glioblastoma in which the diagnosis was delayed as long as 17 months after ICH. A 62-year-old man presented with a headache and aphasia. Computed tomography revealed ICH in the left temporal lobe. Magnetic resonance (MR) images revealed that the hematoma had a mix of isointense and surrounding hypointense lesions on T1-weighted MR images and gadolinium-enhanced lesions at the wall and the septum of the hematoma. An endoscopic evacuation of the hematoma was performed. No causative lesions were found during intraoperative and histological examinations. After seven months, abnormal signals were completely resolved on MR images, except for the small and stable enhanced lesion on three-dimensional gadolinium-enhanced T1-weighted MR imaging (3D Gd-T1WI) at the base of the hematoma, which did not change in size for seven months. However, a large gadolinium-enhanced lesion at the left temporal lobe developed 17 months after ICH. He underwent total resection of the lesion and was diagnosed with glioblastoma. He received radiation therapy and temozolomide but died of disseminated recurrence 31 months after ICH. In conclusion, this report presents a didactic case of glioblastoma in which the diagnosis of glioblastoma was delayed 17 months after ICH whereas hemorrhagic-onset glioblastoma was previously considered ruled out in cases in which six months or more have passed after ICH. In order not to overlook these cases, follow-up with 3D Gd-T1WI is essential in the case of suspected tumor-related ICH and close follow-up is recommended when the enhanced lesion does not resolve after a long period even if it does not grow. Spontaneous intracerebral hemorrhage (ICH) is frequently associated with hypertension, excessive alcohol use, and cerebral amyloid angiopathy . BecauseGlioblastoma is one of the pathologies that frequently can cause spontaneous ICH . In patiThis report presents a didactic case of glioblastoma in which the diagnosis of glioblastoma was delayed 17 months after ICH. Consent for the publication of this case report was obtained from his family, and this study was approved by the ethical board of Tohoku University Hospital (No. 23888).Clinical courseA 62-year-old man, previously diagnosed with hypertension, first complained of headache and aphasia. He was subsequently admitted to another hospital on day three. CT obtained at onset revealed mixed hyperdense and surrounding isodense lesions in the left temporal lobe Figure . He was The nodular lesions were located anteriorly and caudally of the hematoma on three-dimensional gadolinium contrast-enhanced T1WI (3D Gd-T1WI) Figure . From thSeven months after the surgery, the hyperintense area in the cerebral parenchyma on T2WI was completely resolved Figure .Consequently, he underwent left frontotemporal craniotomy and tumor removal. On histological examination, relatively small atypical glial cells, showing marked nuclear atypia and pleomorphic features, proliferated with high cellularity. Microvascular proliferation Figure  and pseuTo the best of our knowledge, this case of hemorrhagic-onset left temporal glioblastoma, IDH wild-type, had the longest latency from hemorrhage to the diagnosis of glioblastoma. He was initially diagnosed with atypical ICH at the left temporal lobe and we presumed that he had causative pathology including malignant glioma, metastatic tumor, or cavernous malformation. Unfortunately, preoperative imaging, intraoperative finding, histological examination, or serial MR imaging by seven months could not detect the underlying glioblastoma in this case.In a report from a single institute and literature review of hemorrhagic-onset glioblastoma ,8, five Findings of the mixed intensity appearance of hematoma on T1WI and T2WI, delayed evolution pattern of the hyperintense area on T1WI, presence of irregular and discontinuous hemosiderin rim, and peripheral linear and nodular enhancement on Gd-T1WI suggest the ICH from the tumor ,18. HoweWe did not consider the residual enhanced lesion at seven months after ICH as glioblastoma because the lesion did not grow for seven months at that time. However, judging from the spatial correlations between the small enhanced lesions and progressive disease, the small enhanced lesion in Figure In conclusion, this report presents a didactic case of glioblastoma in which the diagnosis of glioblastoma was delayed 17 months after ICH whereas hemorrhagic-onset glioblastoma was previously considered ruled out in cases in which six months or more have passed after ICH. In order not to overlook these cases, follow-up with 3D Gd-T1WI is essential in the case of suspected tumor-related ICH and close follow-up is recommended when the enhanced lesion does not resolve after a long period even if it does not grow.


Candidatus Liberibacter asiaticus’ (CLas). Currently, there are no citrus species resistant to CLas. Genetic transformation is one of the most effective approaches used to induce resistance against plant diseases. Antimicrobial peptides (AMPs) have shown potential breakthroughs to improve resistance to bacterial diseases in plants. In this paper, we confirm the Agrobacterium-mediated transformation of Pera sweet orange expressing the AMP sarcotoxin IA (stx IA) gene isolated from the flesh fly Sarcophaga peregrina and its reaction to CLas, involving plant performance and fruit quality assessments. Four independent transgenic lines, STX-5, STX-11, STX-12, and STX-13, and a non-transgenic control, were graft-inoculated with CLas. Based on our findings, none of the transgenic plants were immune to CLas. However, the STX-5 and STX-11 lines showed reduced susceptibility to HLB with mild disease symptoms and low incidence of plants with the presence of CLas. Fruit and juice quality were not affected by the genetic transformation. Further, no residues of the sarcotoxin IA protein were found in the juice of the STX-11 and STX-12 fruits, though detected in the juice of the STX-5 and STX-13 lines, as revealed by the immunoblotting test. However, juices from all transgenic lines showed low traces of sarcotoxin IA peptide in its composition. The accumulation of this peptide did not cause any deleterious effects on plants or in fruit/juice. Our findings reinforce the challenges of identifying novel approaches to managing HLB.Huanglongbing (otherwise known as HLB or greening) is currently the most devastating citrus disease worldwide. HLB is primarily associated with the phloem-inhabiting bacterium ‘ Citrus× sinensis (L.) Osbeck) fruit and juice, accounting for three-quarters of the total sweet orange juice exports . Fu. FuCLas L*. These results were confirmed by the citrus color index (CCI), as a lower value was recorded in the control of the HLB-affected fruit. Interestingly, the majority of the STX IA transgenic fruit did not differ significantly (p ≤ 0.05) regarding CCI despite CLas infections, except for the STX-5 fruit that showed lower CCI for the HLB-affected compared to the non-inoculated ones  ratio is the most acceptable indicator that regulates the sweet orange fruit maturation and harvest season ,71,74. Tstandard .stx IA gene expression , as determined by the indirect ELISA test. The accumulation of this peptide did not cause any deleterious effects on fruit or juice composition, similar to previous report on plants of the same sweet orange cultivar  arranged on a complete randomized design with five replications. All data were processed in R v. 4.0.2  using the ExpDes, FactoMineR, and ggplot2 packages for the graphics and visualization of the statistical data.Fruit and juice quality parameters were assessed in a 2 × 5 factorial [2 treatments (non- or Huanglongbing (HLB) is currently considered the most devastating disease for citrus production and has become a challenge for the scientific community, which has been pressured to develop novel strategies to manage this complex pathosystem. This disease has the potential to corner commercial citrus production. Therefore, the transgenic plants evaluated in this study may represent a promising strategy for managing HLB shortly, particularly with the endemic occurrence of HLB.sarcotoxin IA (stx IA) gene in plant tissues. The Agrobacterium-mediated transformation of the plant using the antimicrobial peptide (AMP) sarcotoxin IA does not induce immunity against ‘Candidatus Liberibacter asiaticus’ (CLas) but reduces its susceptibility by promoting a lower cumulative incidence of CLas-positive plants with moderate symptoms. The fruit and juice quality of the STX IA transgenic lines attends to the quality standards required by the citrus industry. Juice from the STX-11 and STX-12 fruit did not have any sarcotoxin IA protein residues revealed by immunoblotting, only juice from STX-5 and STX-13 fruit. On the other hand, the juice of all transgenic lines showed low traces of sarcotoxin IA peptide, as detected by the indirect ELISA test.The genetic transformation and expression of the gene encoding the sarcotoxin IA (STX IA) peptide were not deleterious to the Pera sweet orange plants and fruit/juice. All STX IA transgenic lines expressed the


This collection highlights a selection of articles published in 2021 from the Lipids in Cardiovascular Disease section of Frontiers in Cardiovascular Medicine. Lipids such as cholesterol and triglycerides (TG) are key contributors to cardiovascular disease (CVD) . The subBardolia et al. provide an insightful narrative review of non-statin therapies that are shown promising in reducing LDL-C, either as monotherapy or in combination therapy with statins or other non-statin medications , or reduce proprotein convertase subtilisin/kexin type 9 (PCSK9) function by preventing its binding to the LDL receptors  or by inhibiting its production by the liver .Lowering of LDL-C had become a target of interest in the reduction of the risk of myocardial infarction and other cardiovascular events . Hydroxyications . They emZhang et al. sought to investigate the potential effects of non-drug therapy with double-filtration plasmapheresis (DFPP) on lipid metabolism-, endoplasmic reticulum (ER) stress-, and apoptosis-related proteins in peripheral blood mononuclear cells (PBMCs) before and after lipid clearance in patients with hyperlipidemia  is a low-cost treatment used to decrease LDL-C concentrations in patients with dyslipidaemias, such as homozygous familial hypercholesterolemia (HoFH) . In theiipidemia . In lineipidemia , they shRecent clinical trial evidence led to the reprioritization of the causal lipids responsible for the onset and progression of atherosclerotic cardiovascular disease . HypertrGuo et al. underscore that there is no consensus on the optimal cutoff value after a daily meal in the diagnosis of HTG in Chinese subjects. In their original article, they thus sought to determine the non-fasting cutoff value that corresponds to the target fasting level of 2.3 mmol/L in Chinese patients. From March 2017 to July 2020, they enrolled a cohort of 602 Chinese patients, including 120 with HTG (TG ≥ 2.3 mmol/L before admission). Blood lipid levels were measured at 0, 2, and 4 h after breakfast. The group reported that the levels of non-fasting TG increased significantly in both HTG and non-HTG subjects, and reached a peak at 4 h post-prandial. ROC curve analysis revealed that the optimal cutoff value used to predict HTG is 2.66 mmol/L, which brings the incidence of non-fasting HTG close to its fasting level , there is no simple, widely available assay to measure the cholesterol content of TG-rich lipoproteins and remnants . Plasma ng level . As a siAdu-Amankwaah et al. underline that ADAM17 cleaves pro-inflammatory cytokines such as tumor necrosis factor α and interleukin 6 and activates nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathways  is a key regulator of inflammation and lipid metabolism in a specific cardiomyopathy, the Takotsubo cardiomyopathy (TTC). This disease consists of an acute, stress-induced cardiac syndrome characterized by a transient wall motion abnormality of the left ventricle . In theipathways . They suAltogether, original articles and reviews included in the 2021 Lipids in Cardiovascular Disease section of Frontiers in Cardiovascular Medicine gather new pathophysiologic insights onto the contribution and management of lipids in CVD.CB wrote the first draft of the manuscript. NT translated the manuscript. CM corrected, edited, and finalized the manuscript. All authors listed approved the work for publication.This work was funded by the Canadian Institutes for Health Research Canada Research Chair (950-232250) and the Montreal Heart Institute Foundation to CM.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. The handling editor MS-T declared a past co-authorship with the authors.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.