bluuebunny/crossref_metadata_2025_split huggingface dataset:
Missile War Injuries of the Craniofacial Region
Authors: Kummoona Raja 
Published: June 2020

Abstract
Many factors govern the nature, severity, and outcome of missile war injuries and associated soft tissue damages. Managements of primary phase and trauma care have improved significantly. Many of these injured victims survived and require immediate care for primary phase management. Secondary phase was achieved by reconstruction of soft tissue by local, regional flaps, and bony defect by bone grafting.
There is no consensus on timing of treatment of bone and soft tissue of missile war injuries.
Currently, in Iraq, anti-government's protestors’ movement for the last 3 months mainly unemployed young people demanding for human rights has resettled in 22,000 people being injured. This includes more than 600 young men who were assassinated by unknown killers through confrontation with security and police men using tear gas canisters and sound bombs. The demonstrators used mini cars (Tuck Tuck) for attacking policemen and security people and used them for transferring injured demonstrators as ambulance to a special tent in the Tahrir Square for receiving first aid.
A Three-Dimensional Study of the Nasolabial Soft Tissue Symmetry in Children With Unilateral Complete Cleft Lip and Palate Using Traditional and Split-Type Nasoalveolar Molding
Authors: Cai Donglin , Zheng Jie , Kuang Wenying , Li Zhelun , Yuan Shiyu , Xiong Hui , Yuan Wenjun 
Published: June 2020

Background:
Presurgical nasoalveolar molding (NAM) is the most common preoperative treatment for cleft lip and palate. However, NAM may have some limitations such as requiring high technical sensitivity and frequent visits. To simplify the device, some scholars have changed the traditional NAM into a split-NAM consisting of a alveolar molding plate and a nasal hook. This study compared the shaping effect of split NAM and traditional NAM on nasolabial soft tissue using three-dimensional (3D) measurement.

Methods:
A total of 39 patients with unilateral cleft lip and palate (UCLP) were enrolled and divided into 2 groups. 13 patients were treated with split-NAM while the other 26 patients were treated with traditional NAM. 3D images of all patients’ craniofacial soft tissue before and after NAM treatment were recorded and measured by three-dimensional software. Statistical analysis of measurements in both groups was performed using SPSS software.

Results:
After treatment, nasal soft tissue symmetry in the split-NAM group was better improved than that in the NAM group in vertical and anterior-posterior direction, but was worse improved in transverse direction. There was no significant difference in labial soft tissue symmetry between two groups.

Conclusions:
The split NAM can better elevate the alar and nostrils of the cleft side, and have a better forward effect on alar outer edge, nasal base, and nostrils. However, the traditional NAM can better reduce the width of nasal base.
Assessment of Maxillary Sinus Changes After Le Fort I Osteotomy Surgery
Authors: Akbulut Nihat , Kurşun Çakmak Emine Şebnem , Bayrak Seval 
Published: June 2020

Objective:The goal of this retrospective study is to examine the changes of maxillary sinus volume, sinus membrane thickness (SMT) and the distance between the floor of maxillary sinus and ostium after Le Fort I osteotomy.Methods:A total of 30 patients who underwent Le Fort I osteotomy were evaluated just before and 1 year after the surgical operation. Linear and volumetric measurements were done via 3D-DOCTOR software on sectional and 3D images.Results:Decrease in maxillary sinus volume, increase in SMT and no change in distance between the floor of the maxillary sinus and ostium were detected after surgery. After surgery, SMT was found higher in advancement + impaction group.Conclusion:This paper clarified that Le Fort I osteotomy affects the volume and thickness of the maxillary sinuses that may lead to deterioration of the ciliary activity and failure in the drainage which are predisposing factors for sinus pathologies. In maxillary osteotomies of later ages, maxillary sinus examination and follow-up should be performed regularly in order to maintain sinus health.
The Impact of Mental Illness on Postoperative Outcomes Among Medicare Beneficiaries
Authors: Paredes Anghela Z. , Hyer J. Madison , Diaz Adrian , Tsilimigras Diamantis I. , Pawlik Timothy M. 
Published: June 2020

Objective:
The aim of this study was to define the prevalence of preexisting mental illness, as well as characterize the impact of a preexisting mental illness diagnosis on postoperative outcomes.

Summary Background Data:
Preoperative surgical evaluation and risk stratification have traditionally centered on optimizing physical health. The influence of mental health on postoperative surgical outcomes has not been investigated.

Methods:
Medicare beneficiaries who underwent elective colectomy, coronary artery bypass grafting, abdominal aortic aneurysm repair, abdominal aortic aneurysm repair, total hip arthroplasty, total knee arthroplasty, and lung resection were identified. Patients were classified as having mental illness using International Classification of Diseases, 9

th

and 10

th

Revisions Procedures codes (ICD9/10CM) codes for anxiety, depression, bipolar disorder, schizophrenia, or other psychotic disorder.

Results:
Among 1,889,032 Medicare beneficiaries who met inclusion criteria 560,744 (n = 29.7%) individuals had an antecedent diagnosis of mental illness. The majority had anxiety and/or depression (91.8%), whereas a smaller subset (8.2%) had a severe mental illness diagnosis. Patients who did and did not have mental illness were comparable relative to age and comorbidities. Patients with preoperative mental illness had a higher chance of surgical complications [anxiety/depression odds ratio (OR) 1.44, 95% confidence interval (CI) 1.42–1.46, severe mental illness OR 1.71, 95%CI 1.66–1.77] and an extended length of stay (anxiety/depression OR 1.45, 95% CI 1.44–1.46, severe mental illness OR 2.34, 95% CI 2.28–2.39). History of anxiety/depression (OR 1.87, 95% CI 1.85–1.90) or severe mental illness (OR 2.86, 95% CI 2.77–2.94) was also associated with higher odds of 30-day readmission. Additionally, individuals with mental illness had a higher prevalence of suicidal ideation within the first year after surgery (no mental illness: 1.88 per 100,000 individuals; anxiety/depression: 51.3 per 100,000 individuals; severe mental illness: 238.9 per 100,000 individuals).

Conclusions:
Three in 10 Medicare beneficiaries had a preexisting mental illness diagnosis, which was strongly associated with worse postoperative outcomes, as well as suicide risk. Surgeons need to optimize mental health assessment and services in the preoperative setting to improve outcomes for this vulnerable population.
Trends in mortality of alcoholic liver disease among adults in the United States, 1999-2017
Authors: Ryu Emily , Xia Harry H. , Guo Grace L , Zhang Lanjing 
Published: June 2020

AbstractSome subtypes of alcoholic liver disease (ALD) recently had increasing prevalence or mortality. Prevalence of alcoholic fatty liver disease was increased. Mortality of alcoholic hepatitis and cirrhosis also had upward trends. However, trends in ALD- mortality and related factors are unclear. We therefore examined trends in age-standardized ALD-mortality among U.S. adults by factors using multivariable piecewise log-linear models. We collected mortality-data (age-standardized for the 2000 U.S. standard population) from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research database (CDC WONDER), using the Multiple Cause of Death Data to identify all ALD deaths in the United States for 1999-2017. We identified 296,194 deaths of ALD during 1999-2017. Trends in multivariable-adjusted, age-standardized mortality did not differ by sex, race, age or urbanization. The age-standardized mortality ratios of male/female, White/non-White and Metropolitan/Non-Metropolitan were 2.346, 1.657 and 0.851 in 2017, respectively. Strikingly, our multivariable model showed that subjects of 65+ years had the highest and the fastest growing mortality in the 3 age-groups. These findings highlight the continuation of health disparities in ALD, particularly in elderly subjects. Further works are warranted to validate and delineate the associated factors.
Rapid SARS-CoV-2 testing in primary material based on a novel multiplex LAMP assay
Authors: Schermer Bernhard , Fabretti Francesca , Damagnez Maximilian , Di Cristanziano Veronica , Heger Eva , Arjune Sita , Tanner Nathan A. , Imhof Thomas , Koch Manuel , Ladha Alim , Joung Julia , Gootenberg Jonathan S. , Abudayyeh Omar O. , Burst Volker , Zhang Feng , Klein Florian , Benzing Thomas , Müller Roman-U. 
Published: June 2020

AbstractBackgroundRapid and extensive testing of large parts of the population and specific subgroups is crucial for proper management of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and decision-making in times of a pandemic outbreak. However, point-of-care (POC) testing in places such as emergency units, outpatient clinics, airport security points or the entrance of any public building is a major challenge. The need for thermal cycling and nucleic acid isolation hampers the use of standard PCR-based methods for this purpose.MethodsTo avoid these obstacles, we tested PCR-independent methods for the detection of SARS-CoV-2 RNA from primary material (nasopharyngeal swabs) including loop-mediated isothermal amplification (LAMP) and specific high-sensitivity enzymatic reporter unlocking (SHERLOCK).ResultsWhilst specificity of standard LAMP assays appears to be satisfactory, sensitivity does not reach the current gold-standard quantitative real-time polymerase chain reaction (qPCR) assays yet. We describe a novel multiplexed LAMP approach and validate its sensitivity on primary samples. This approach allows for fast and reliable identification of infected individuals. Primer optimization and multiplexing helps to increase sensitivity significantly. In addition, we directly compare and combine our novel LAMP assays with SHERLOCK.ConclusionIn summary, this approach reveals one-step multiplexed LAMP assays as a prime-option for the development of easy and cheap POC test kits.
Validation of a new approach for distinguishing anesthetized from awake state in patients using Directed Transfer Function applied to raw EEG
Authors: Juel Bjørn E. , Romundstad Luis , Storm Johan F. , Larsson Pål G. 
Published: June 2020

AbstractAimIn a previous study, we found that the state of wakefulness in patients undergoing general anesthesia with propofol can effectively be monitored with high temporal resolution using an automatic measure of connectivity based on the Directed Transfer Function (DTF) calculated from short segments of electroencephalography (EEG) time-series. The study described here was designed to test whether the same measure can be used to monitor the state of the patients also during sevoflurane anesthesia.MethodsTwenty-five channel EEG recordings were collected from 8 patients undergoing surgical anesthesia with sevoflurane. The EEG data were segmented into one second epochs and labeled as awake or anesthetized in accordance with the clinician’s judgement, and the sensor space directed connectivity was quantified for every epoch using the DTF. The resulting DTF derived connectivity parameters were compared to corresponding parameters from our previous study using permutation statistics. A data driven classification algorithm was then employed to objectively classify the individual 1-second epochs as coming from awake or anesthetized state, using a leave-one-out cross-validation approach. The classifications were made for every epoch using the median DTF parameters across the five preceding 1-second EEG epochs.ResultsThe DTF derived connectivity parameters showed a significant difference between the awake and sevoflurane-induced general anesthesia at the group level (p<0.05). In contrast, the DTF parameters were not significantly different when comparing sevoflurane and propofol data neither in the awake nor in anesthetized state (p>0.05 for both comparisons). The classification algorithm reached a maximum accuracy of 96.8% (SE=0.63%). Optimizing the algorithm for simultaneously having high sensitivity and specificity in classification reduced the accuracy to 95.1% (SE=0.96%), with sensitivity of 98.4% (SE=0.80%) and specificity of 94.8% (SE=0.10%).ConclusionThese findings indicate that the DTF changes in a similar manner when humans undergo general anesthesia caused by two distinct anesthetic agents with different molecular mechanisms of action. This seems to support the idea that brain connectivity is related to the level of consciousness in humans, although further studies are needed to clarify whether our results may be contaminated by confounding factors.
Covid19 infection spread in Greece: Ensemble forecasting models with statistically calibrated parameters and stochastic noise
Authors: Politis Georgios D. , Hadjileontiadis Leontios 
Published: June 2020

AbstractFollowing the outbreak of the novel coronavirus SARS-Cov2 in Europe and the subsequent failure of national healthcare systems to sufficiently respond to the fast spread of the pandemic, extensive statistical analysis and accurate forecasting of the epidemic in local communities is of primary importance in order to better organize the social and healthcare interventions and determine the epidemiological characteristics of the disease. For this purpose, a novel combination of Monte Carlo simulations, wavelet analysis and least squares optimization is applied to a known basis of SEIR compartmental models, resulting in the development of a novel class of stochastic epidemiological models with promising short and medium-range forecasting performance. The models are calibrated with the epidemiological data of Greece, while data from Switzerland and Germany are used as a supplementary background. The developed models are capable of estimating parameters of primary importance such as the reproduction number and the real magnitude of the infection in Greece. A clear demonstration of how the social distancing interventions managed to promptly restrict the epidemic growth in the country is included. The stochastic models are also able to generate robust 30-day and 60-day forecast scenarios in terms of new cases, deaths, active cases and recoveries.
Deep Learning Improves Pre-Surgical White Matter Visualization in Glioma Patients
Authors: Panesar Sandip S , Nath Vishwesh , Pathak Sudhir K , Schneider Walter , Landman Bennett A. , Iv Michael , Anthony Diana , Jansen Tatiana , Abhinav Kumar , Fernandez-Miranda Juan 
Published: June 2020

BackgroundDiffusion tensor imaging (DTI) is a commonly utilized pre-surgical tractography technique. Despite widespread use, DTI suffers from several critical limitations. These include an inability to replicate crossing fibers and a low angular-resolution, affecting quality of results. More advanced, non-tensor methods have been devised to address DTI’s shortcomings, but they remain clinically underutilized due to lack of awareness, logistical and cost factors.ObjectiveNath et al. (2020) described a method of transforming DTI data into non-tensor high-resolution data, suitable for tractography, using a deep learning technique. This study aims to apply this technique to real-life tumor cases.MethodsThe deep learning model utilizes a residual convolutional neural network architecture to yield a spherical harmonic representation of the diffusion-weighted MR signal. The model was trained using normal subject data. DTI data from clinical cases were utilized for testing: Subject 1 had a right-sided anaplastic oligodendroglioma. Subject 2 had a right-sided glioblastoma. We conducted deterministic fiber tractography on both the DTI data and the post-processed deep learning algorithm datasets.ResultsGenerally, all tracts generated using the deep learning algorithm dataset were qualitatively and quantitatively (in terms of tract volume) superior than those created with DTI data. This was true for both test cases.ConclusionsWe successfully utilized a deep learning technique to convert standard DTI data into data capable of high-angular resolution tractography. This method dispenses with specialized hardware or dedicated acquisition protocols. It presents an economical and logistically feasible method for increasing access to high definition tractography imaging clinically.
Fuzzy logic assisted COVID 19 safety assessment of dental care
Authors: Adwibowo Andrio 
Published: June 2020

AbstractUncertainty is significant when assessing a risk of certain health care facility conditions especially the facility that prone to the COVID 19 risk. One solution to deal with an uncertainty in health situation assessment is through fuzzy inference system. For that reason, this study aims to develop fuzzy assisted system to assess the safety of dental care related to the sets of patient and environmental conditions. The fuzzy system allows assessment based on the patient’s body temperature, travel history, dental care ventilation rate, and disinfection frequency. The fuzzy system incorporates several steps including fuzzification, fuzzy regulation, and defuzzification. As a result of this study, the fuzzy system is able to assess and identify the risk of dental care according to the patient’s health status and hygiene conditions of dental care as well. To conclude, fuzzy system used in this study has offered the advantage of assessing at any situation as for patient and environmental factor predicts the safety of dental care.
Reproducing the long term predictions from Imperial College CovidSim Report 9
Authors: Rice Ken , Wynne Ben , Martin Victoria , Ackland Graeme 
Published: June 2020

1AbstractWe present calculations using the CovidSim code which implements the Imperial College individual-based model of the COVID epidemic. Using the parameterization assumed in March 2020, we reproduce the predictions presented to inform UK government policy in March 2020. We find that CovidSim would have given a good forecast of the subsequent data if a higher initial value of R0 had been assumed. We then investigate further the whole trajectory of the epidemic, presenting results not previously published. We find that while prompt interventions are highly effective at reducing peak ICU demand, none of the proposed mitigation strategies reduces the predicted total number of deaths below 200,000. Surprisingly, some interventions such as school closures were predicted to increase the projected total number of deaths.
Polymorphisms in the ACE2 Locus Associate with Severity of COVID-19 Infection
Authors: Wooster Luke , Nicholson Christopher J. , Sigurslid Haakon H. , Lino Cardenas Christian L. , Malhotra Rajeev 
Published: June 2020

AbstractData from clinical studies suggests a strong association between underlying cardiometabolic disease and worse outcomes in COVID-19. Given that the SARS-CoV-2 virus has a unique marked affinity to the human angiotensin-converting enzyme 2 (ACE2) receptor, one potential explanation behind this phenomenon may involve the higher expression of ACE2 receptor in these patients. Here, we analyzed association between polymorphisms in the ACE2 locus and COVID-19 severity in 62 patients found to be COVID-19 positive by polymerase chain reaction. Of these patients, 23 required hospitalization due to COVID-19 infection. Of 61 ACE2 single nucleotide polymorphisms (SNPs) genotyped in this patient cohort, 10 were significantly associated with tissue expression of ACE2. Logistic regression adjusted for age and for sex identified six of these ten SNPs to be significantly associated with hospitalization. These results provide preliminary evidence of a genetic link between the ACE2 genotype and COVID-19 disease severity and suggest that the ACE2 genotype may inform COVID-19 risk stratification and need for more intense therapy.
An integrated multi-omics analysis identifies clinically relevant molecular subtypes of non-muscle-invasive bladder cancer
Authors: Lindskrog Sia Viborg , Prip Frederik F. , Lamy Philippe , Taber Ann , Groeneveld Clarice S. , Birkenkamp-Demtröder Karin , Jensen Jørgen Bjerggaard , Strandgaard Trine , Nordentoft Iver , Christensen Emil , Sokac Mateo , Birkbak Nicolai J. , Maretty Lasse , Hermann Gregers G. , Petersen Astrid C. , Weyerer Veronika , Grimm Marc-Oliver , Horstmann Marcus , Sjödahl Gottfrid , Höglund Mattias , Steiniche Torben , Mogensen Karin , de Reyniès Aurélien , Nawroth Roman , Jordan Brian , Lin Xiaoqi , Dragicevic Dejan , Ward Douglas G. , Goel Anshita , Hurst Carolyn D. , Raman Jay D. , Warrick Joshua I. , Segersten Ulrika , Sikic Danijel , van Kessel Kim E.M. , Maurer Tobias , Meeks Joshua J. , DeGraff David J. , Bryan Richard T. , Knowles Margaret A. , Simic Tatjana , Hartmann Arndt , Zwarthoff Ellen C. , Malmström Per-Uno , Malats Núria , Real Francisco X. , Dyrskjøt Lars 
Published: June 2020

AbstractThe molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we performed a large integrative multi-omics analysis of patients diagnosed with NMIBC (n=834). Transcriptomic analysis identified four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provided independent prognostic value beyond established prognostic clinicopathological parameters. High chromosomal instability, p53-pathway disruption and APOBEC-related mutations were significantly associated with transcriptomic class 2a and poor outcome. RNA-derived immune cell infiltration was associated with chromosomally unstable tumors and enriched in class 2b. Spatial proteomics analysis confirmed the higher infiltration of class 2b tumors and demonstrated an association between higher immune cell infiltration and lower recurrence rates. Finally, a single-sample classification tool was built and the independent prognostic value of the transcriptomic classes was documented in 1306 validation samples. The classifier provides a framework for novel biomarker discovery and for optimizing treatment and surveillance in next-generation clinical trials.
The Covid-19 epidemic in the UK
Authors: Faggio Giulia , Peracchi Franco 
Published: June 2020

AbstractIn this note we present some stylised facts about the Covid-19 epidemic in the UK using daily time-series data published by Public Health England and the UK Department of Health and Social Care. We model the data on confirmed new cases using standard count-data models estimated at the country and national levels using a fixed rolling window to capture changes in the model parameters over time. We then use the most recent estimated models to carry out a simple real-time forecasting exercise aimed at predicting the date when the number of confirmed new cases will be approximately zero.
A Standard Virus Load Function
Authors: Hillen Thomas 
Published: June 2020

AbstractThe idea is to design a simple function that can describe typical virus-load curves without solving a full virus load dynamic model. We present such a standard virus load function and validate it on data from influenza A as well as SARS-CoV-2 infection data for Macaque monkeys and humans. Further, we compare the virus load function to an established target model of virus dynamics as presented by A. Smith in [1]. This virus-load function can be used as input to higher level models for the physiological effects of a virus infection, for models for tissue damage, and to develop treatment strategies.