bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Passive microwave Empirical cold Surface Classification Algorithm (PESCA): application to GMI and ATMS
Authors: Camplani Andrea , Casella Daniele , Sanò Paolo , Panegrossi Giulia 
Published: April 2021

AbstractThis paper describes a new Passive microwave Empirical cold Surface Classification Algorithm (PESCA) developed for snow cover detection and characterization by using passive microwave satellite measurements. The main goal of PESCA is to support the retrieval of falling snow, as several studies have highlighted the influence of snow cover radiative properties on the falling snow passive microwave signature. The developed methodology is based on the exploitation of the lower frequency channels (< 90 GHz), common to most microwave radiometers. The methodology applied to the conically scanning GMI and the cross-track scanning ATMS is described in this paper. PESCA is based on a decision tree developed using an empirical method and verified using the AutoSnow product built from satellite measurements. The algorithm performance appears to be robust for both sensors in dry conditions (TPW < 10 mm), and for mean surface elevation < 2500 m, independently of the cloud cover. The algorithm shows very good performance for cold temperatures (2 m temperature below 270 K) with a rapid decrease of the detection capabilities between 270 K and 280 K, where 280 K is assumed as the maximum temperature limit for PESCA [overall detection statistics: POD=0.98(0.92), FAR=0.01(0.08), HSS=0.72(0.69) for ATMS(GMI)]. Some inconsistencies found between the snow categories identified with the two radiometers are related to their different viewing geometry, spatial resolution, and temporal sampling. The spectral signatures of the different snow classes appear to be different also at high frequency (>90GHz), indicating potential impact for snowfall retrieval. This method can be applied to other conically and cross track scanning radiometers including the future operational EPS-SG mission microwave radiometers.
A Neural-Network Quality Control scheme for improved Quantitative Precipitation Estimation accuracy on the UK weather radar network
Authors: Husnoo Nawal , Darlington Timothy , Torres Sebastián , Warde David 
Published: April 2021

AbstractIn this work, we present a new Quantitative-Precipitation-Estimation (QPE) quality-control (QC) algorithm for the UK weather radar network. The real-time adaptive algorithm uses a neural network (NN) to select data from the lowest useable elevation scan to optimize the combined performance of two other radar data correction algorithms: ground clutter mitigation (using CLEAN-AP) and vertical profile of reflectivity (VPR) correction. The NN is trained using 3D tiles of observed uncontaminated weather signals that are systematically combined with ground-clutter signals collected under dry weather conditions. This approach provides a way to simulate radar signals with a wide range of clutter contamination conditions and with realistic spatial structures while providing the uncontaminated “truth” with respect to which the performance of the QC algorithm can be measured. An evaluation of QPE products obtained with the proposed QC algorithm demonstrates superior performance as compared to those obtained with the QC algorithm currently used in operations. Similar improvements are also illustrated using radar observations from two periods of prolonged precipitation, showing a better balance between overestimation errors from using clutter-contaminated low-elevation radar data and VPR-induced errors from using high-elevation radar data.
Otopathologic Abnormalities in CHARGE Syndrome
Authors: da Costa Monsanto Rafael , Knoll Renata Malimpensa , de Oliveira Penido Norma , Song Grace , Santos Felipe , Paparella Michael Mauro , Cureoglu Sebahattin 
Published: April 2021

ObjectiveTo perform an otopathologic analysis of temporal bones (TBs) with CHARGE syndrome.Study DesignOtopathologic study of human TB specimens.SettingOtopathology laboratories.MethodsFrom the otopathology laboratories at the University of Minnesota and Massachusetts Eye and Ear Infirmary, we selected TBs from donors with CHARGE syndrome. These TBs were serially sectioned at a thickness of 20 µm, and every 10th section was stained with hematoxylin and eosin. We performed otopathologic analyses of the external ear, middle ear (middle ear cleft, mucosal lining, ossicles, mastoid, and facial nerve), and inner ear (cochlea, vestibule, internal auditory canal, and cochlear and vestibular nerves). The gathered data were statistically analyzed.ResultsOur study included 12 TBs from 6 donors. We found a high prevalence of abnormalities affecting the ears. The most frequent findings were stapes malformation (100%), aberrant course of the facial nerve (100%) with narrow facial recess (50%), sclerotic and hypodeveloped mastoids (50%), cochlear (100%) and vestibular (83.3%) hypoplasia with aplasia of the semicircular canals, hypoplasia and aplasia of the cochlear (66.6%) and vestibular (91.6%) nerves, and narrowing of the bony canal of the cochlear nerve (66.6%). The number of spiral ganglion and Scarpa’s ganglion neurons were decreased in all specimens (versus normative data).ConclusionsIn our study, CHARGE syndrome was associated with multiple TB abnormalities that may severely affect audiovestibular function and rehabilitation.
The P450 multigene family of Fontainea and insights into diterpenoid synthesis
Authors: Mitu Shahida A. , Ogbourne Steven M. , Klein Anne H. , Tran Trong D. , Reddell Paul W. , Cummins Scott F. 
Published: April 2021

Abstract
Background
Cytochrome P450s (P450s) are enzymes that play critical roles in the biosynthesis of physiologically important compounds across all organisms. Although they have been characterised in a large number of plant species, no information relating to these enzymes are available from the genus Fontainea (family Euphorbiaceae). Fontainea is significant as the genus includes species that produce medicinally significant epoxy-tigliane natural products, one of which has been approved as an anti-cancer therapeutic.

Results
A comparative species leaf metabolome analysis showed that Fontainea species possess a chemical profile different from various other plant species. The diversity and expression profiles of Fontainea P450s were investigated from leaf and root tissue. A total of 103 and 123 full-length P450 genes in Fontainea picrosperma and Fontainea venosa, respectively (and a further 127/125 partial-length) that were phylogenetically classified into clans, families and subfamilies. The majority of P450 identified are most active within root tissue (66.2% F. picrosperma, 65.0% F. venosa). Representatives within the CYP71D and CYP726A were identified in Fontainea that are excellent candidates for diterpenoid synthesis, of which CYP726A1, CYP726A2 and CYP71D1 appear to be exclusive to Fontainea species and were significantly more highly expressed in root tissue compared to leaf tissue.

Conclusion
This study presents a comprehensive overview of the P450 gene family in Fontainea that may provide important insights into the biosynthesis of the medicinally significant epoxy-tigliane diterpenes found within the genus.
Tricuspid regurgitation in ischemic mitral regurgitation patients: prevalence, predictors for outcome and long-term follow-up
Authors: Koren Ofir , Darawsha Henda , Rozner Ehud , Benhamou Daniel , Turgeman Yoav 
Published: April 2021

Abstract
Background
Functional tricuspid regurgitation (FTR) is common in left-sided heart pathology involving the mitral valve. The incidence, clinical impact, risk factors, and natural history of FTR in the setting of ischemic mitral regurgitation (IMR) are less known.

Method
We conducted a cohort study based on data collected from January 2012 to December 2014. Patients diagnosed with IMR were eligible for the study. The median follow-up was 5 years. The primary outcome is defined as FTR developing at any stage.

Results
Among the 134 IMR patients eligible for the study, FTR was detected in 29.9% (N = 40, 20.0% mild, 62.5% moderate, and 17.5% severe). In the FTR group, the average age was 60.7 ± 9.2 years (25% females), the mean LV ejection fraction (LVEF) was 37.3 ± 6.45 [%], LA area 46.4 ± 8.06 (mm2), LV internal diastolic diameter (LVIDD) 59.6 ± 3.94 (mm), RV fractional area change 22.3 ± 4.36 (%), systolic pulmonary artery pressure (SPAP) 48.4 ± 9.45 (mmHg). Independent variables associated with FTR development were age ≥ 65y [OR 1.2], failed revascularization, LA area ≥ 42.5 (mm2) [OR 17.1], LVEF ≤ 24% [OR 32.5], MR of moderate and severe grade [OR 419.4], moderate RV dysfunction [OR 91.6] and pulmonary artery pressure of a moderate or severe grade [OR 33.6]. During follow-up, FTR progressed in 39 (97.5%) patients. Covariates independently associated with FTR progression were lower LVEF, RV dysfunction, and PHT of moderate severity. LA area and LVIDD were at the margin of statistical significance (p = 0.06 and p = 0.05, respectively).

Conclusion
In our cohort study, FTR development and progression due to IMR was a common finding. Elderly patients with ischemic MR following unsuccessful PCI are at higher risk. FTR development and severity are directly proportional to LV ejection fraction, to the extent of mitral regurgitation, and SPAP. FTR tends to deteriorate in the majority of patients over a mean of 5-y follow-up.
Generative adversarial networks for imputing missing data for big data clinical research
Authors: Dong Weinan , Fong Daniel Yee Tak , Yoon Jin-sun , Wan Eric Yuk Fai , Bedford Laura Elizabeth , Tang Eric Ho Man , Lam Cindy Lo Kuen 
Published: April 2021

Abstract
Background
Missing data is a pervasive problem in clinical research. Generative adversarial imputation nets (GAIN), a novel machine learning data imputation approach, has the potential to substitute missing data accurately and efficiently but has not yet been evaluated in empirical big clinical datasets.

Objectives
This study aimed to evaluate the accuracy of GAIN in imputing missing values in large real-world clinical datasets with mixed-type variables. The computation efficiency of GAIN was also evaluated. The performance of GAIN was compared with other commonly used methods, MICE and missForest.

Methods
Two real world clinical datasets were used. The first was that of a cohort study on the long-term outcomes of patients with diabetes (50,000 complete cases), and the second was of a cohort study on the effectiveness of a risk assessment and management programme for patients with hypertension (10,000 complete cases). Missing data (missing at random) to independent variables were simulated at different missingness rates (20, 50%). The normalized root mean square error (NRMSE) between imputed values and real values for continuous variables and the proportion of falsely classified (PFC) for categorical variables were used to measure imputation accuracy. Computation time per imputation for each method was recorded. The differences in accuracy of different imputation methods were compared using ANOVA or non-parametric test.

Results
Both missForest and GAIN were more accurate than MICE. GAIN showed similar accuracy as missForest when the simulated missingness rate was 20%, but was more accurate when the simulated missingness rate was 50%. GAIN was the most accurate for the imputation of skewed continuous and imbalanced categorical variables at both missingness rates. GAIN had a much higher computation speed (32 min on PC) comparing to that of missForest (1300 min) when the sample size is 50,000.

Conclusion
GAIN showed better accuracy as an imputation method for missing data in large real-world clinical datasets compared to MICE and missForest, and was more resistant to high missingness rate (50%). The high computation speed is an added advantage of GAIN in big clinical data research. It holds potential as an accurate and efficient method for missing data imputation in future big data clinical research.

Trial registration
ClinicalTrials.gov ID: NCT03299010; Unique Protocol ID: HKUCTR-2232
COVID-19 as the sole cause of death is uncommon in frail home healthcare individuals: a population-based study
Authors: Nilsson Lena , Andersson Christer , Sjödahl Rune 
Published: April 2021

Abstract
Background
During the first pandemic wave, Sweden experienced a high mortality rate. Home healthcare reflects a group of people especially vulnerable to coronavirus disease 2019 (COVID-19). We aimed to evaluate the pattern of comorbidity and frailty in a group of individuals having fatal outcomes in home healthcare during the COVID-19 pandemic March to September 2020, and to assess the contribution of COVID-19 in the fatal outcomes.

Methods
A cohort of adults with confirmed COVID-19 diagnosis that deceased in home healthcare between March and September 2020 were analysed in a retrospective study comprising home healthcare in 136 facilities in one Swedish county. Main outcome measures were comorbidity and frailty.

Results
One hundred fifty-five individuals (88 women, 67 men) aged 57–106 (median 88) years were included in the analysis. Nine had considerable frailty (ability to perform various activities of daily living but confined to bed or chair on occasion) and the remaining 146 had severe frailty (unable to perform activities of daily living and/or confined to bed or chair; dementia necessitating care). Three or more diagnoses besides COVID-19 were present in 142 individuals and another eight had two diagnoses in addition to COVID-19. In 20 (13%) individuals, COVID-19 was assessed as the principal cause of death, in 100 (64.5%) a contributing cause, and for the remaining 35 (22.5%) death was probably caused by another comorbidity. This seemed to change over the course of the COVID − 19 pandemic, with its contributing role decreasing from the middle of the summer.

Conclusions
Death in home healthcare during the first wave of the pandemic mostly affected individuals with severe frailty and comorbidity at very advanced ages. One fifth of the individuals who died in home health care had another cause than Covid-19.

Trial registration
Clinical Trials.gov NCT04642196 date 24/11/2020.
The characteristics of laboratory tests at admission and the risk factors for adverse clinical outcomes of severe and critical COVID-19 patients
Authors: Wang Liulin , Cheng Xiaobin , Dong Qiufen , Zhou Chenliang , Wang Yeming , Song Bin , Li Weinan , Wang Min , Qin Rui , Long Qi , Liu Juan , Li Jing , Li Dan , Li Gang , Ba Yuanming 
Published: April 2021

Abstract
Background
The current coronavirus disease 2019 (COVID-19) is a public health emergency. In this study, we aimed to evaluate the risk factors for mortality in severe and critical COVID-19 patients.

Methods
We performed a retrospective study of patients diagnosed with severe and critical COVID-19 from four hospitals in Wuhan, China, by evaluating the clinical characteristics and laboratory results, and using Cox proportional hazards model to assess the risk factors involved in disease progression.

Results
In total, 446 patients with COVID-19 were enrolled. The study indicated a high mortality rate (20.2%) in severe and critical COVID-19 patients. At the time of admission, all patients required oxygen therapy, and 52 (12%) required invasive mechanical ventilation, of which 50 (96%) died. The univariate Cox proportional hazards model showed a white blood cell count of more than 10 × 109/L (HR 3.993,95%CI 2.469 to 6.459) that correlated with an increased mortality rate. The multivariable Cox proportional hazards model demonstrated that older age (HR 1.066, 95% CI 1.043 to 1.089) and higher white blood cell count (HR 1.135, 95% CI 1.080 to 1.192) were independent risk factors for determining COVID-19 associated mortality.

Conclusions
COVID-19 is associated with a significant risk of morbidity and mortality in the population. Older age and higher white blood cell count were found to be independent risk factors for mortality.
A patient with a homozygous diacylglycerol kinase epsilon (DGKE) gene mutation with atypical haemolytic uraemic syndrome and low C3 responded well to eculizumab: a case report
Authors: Alabdulqader Muneera , Alfakeeh Khalid 
Published: April 2021

Abstract
Background
Atypical haemolytic uraemic syndrome (aHUS) is a rare systemic syndrome characterized by non-immune haemolytic anaemia, thrombocytopenia, and kidney injury. In most cases, alternative complement pathway dysregulation is the identifying cause. Recently, other genetic causes have been identified, including a mutation in the diacylglycerol kinase epsilon (DGKE) gene, which theoretically affect the coagulation pathway and does not affect the complement pathway. Data about the management of these patients are limited. Ideal management and definitive treatment protocols have not yet been established.

Case presentation
A three-year-old boy presented with features of atypical haemolytic uraemic syndrome (aHUS) and low complement C3. He was presumed to have complement-mediated aHUS and was managed empirically with eculizumab. Two weeks after starting eculizumab, his haemoglobin levels, platelet count, and complement C3 level normalized but he continued to have non-nephrotic range proteinuria. His genetic testing revealed a homozygous DGKE mutation, with no other mutation detected. Six months after presentation, the patient was still in remission with no features of aHUS, a trial of weaning eculizumab by increasing dose interval was followed by nephrotic range proteinuria and severe oedema. His proteinuria improved and his oedema resolved after resuming his recommended eculizumab dose.

Conclusions
DGKE gene mutation can lead to aHUS with theoretically no complement dysregulation. However, some patients with this mutation show alternative complement pathway activation. This case report describes a patient with aHUS due to a DGKE gene mutation and low C3 levels who responded to eculizumab, adding to the previously reported cases of patients with DGKE gene mutations who had complete remission with no relapse with C5 blockers and/or plasma exchange. A randomized controlled study on patients with DGKE mutations might be beneficial in understanding the disease and generating a management protocol.
Comorbidity of depression and anxiety leads to a poor prognosis following angina pectoris patients: a prospective study
Authors: Bai Bingqing , Yin Han , Guo Lan , Ma Huan , Wang Haochen , Liu Fengyao , Liang Yanting , Liu Anbang , Geng Qingshan 
Published: April 2021

Abstract
Background
Depression and anxiety are two common mood problems among patients with cardiovascular disease (CVD) and are associated with poor cardiac prognoses. The comorbidity of depression and anxiety is considered to be a more severe psychological status than non-comorbid mood disorders. However, little is known about the relationship between depression or anxiety and noncardiac readmission. We conducted a prospective study on the prognostic impact of depression, anxiety, and the comorbidity of the two among angina pectoris (AP) patients.

Method
In this prospective study, 443 patients with AP were included in the analysis. Follow-up assessments were performed 1 year, and 2 years after patient discharges. Clinical outcomes of interest included noncardiac readmission, major adverse cardiovascular events (MACEs), and composite events. Depression and anxiety symptom scores derived from the patient health questionnaire-9 (PHQ-9) and generalised anxiety disorder-7 (GAD-7) questionnaire were used to assess mood symptoms at baseline. Participants with symptom scores of ≥10 on both the depression and anxiety questionnaires formed the clinical comorbidity subgroup. We used multivariable Cox proportional hazards models to evaluate the impact of individual mood symptom and comorbidity on clinical outcomes.

Results
Among all the AP patients, 172 (38. 9%) were determined to have depression symptoms, 127 (28.7%) patients had anxiety symptoms and 71 (16.0%) patients suffered from their comorbidity. After controlling covariates, we found that patients who endured clinical depression (hazard ratio [HR] = 2.38, 95% confidence interval [CI] 1.06–5.33, p = 0.035) and anxiety ([HR] 2.85, 95% [CI] 1.10–7.45, p = 0.032) had a high risk of noncardiac readmission. Compared to participants with no mood symptoms, those with clinical comorbidity of depression and anxiety presented a greater risk of noncardiac readmission ([HR] 2.91, 95% [CI] 1.03–8.18, p = 0.043) MACEs ([HR] 2.38, 95% [CI] 1.11–5.10, p = 0.025) and composite event ([HR] 2.52, 95% [CI] 1.35–4.69, p = 0.004).

Conclusion
Depression and anxiety were found to have predictive value for noncardiac readmission among patients with AP. Furthermore, prognoses were found to be worse for patients with comorbidity of depression and anxiety than those with single mood symptom. Additional attention needs to be focused on the initial identification and long-term monitoring of mood symptom comorbidity.
Medical thoracoscopy treatment for pleural infections: a systematic review and meta-analysis
Authors: Mondoni Michele , Saderi Laura , Trogu Federica , Terraneo Silvia , Carlucci Paolo , Ghelma Filippo , Centanni Stefano , Sotgiu Giovanni 
Published: April 2021

Abstract
Background
Complicated parapneumonic effusions and empyema represent advanced stages of pleural infections and are characterized by a high mortality. Medical thoracoscopy is a safe and minimally invasive endoscopic technique prescribed to treat severe pleural infections. However, only a few studies evaluated its success rate. A systematic review of observational studies was performed to assess the efficacy of medical thoracoscopy in patients with complicated parapneumonic effusions and empyema, as well as its predictive factors.

Methods
A search of the scientific evidence was carried out using PubMed, EMBASE, and Cochrane Central Register of Controlled Trials. Articles describing observational studies on medical thoracoscopy in patients with parapneumonic effusions and empyema were selected.

Results
Eight studies met the inclusion criteria. The pooled treatment success rate of thoracoscopy was 85% (95% CI 80.0–90.0%; I2: 61.8%) when used as first-line intervention or after failure of chest tube. The pooled complication rate was 9.0% (95% CI 6.0–14.0%; I2: 58.8%). A pooled difference of treatment success of 9.0% (95% CI 1.0–18.0%) was found when post-thoracoscopy intra-pleural fibrinolysis was prescribed. Pooled success rate was higher in cases with pleural fluid culture negativity (pooled difference: 14.0%; 95% CI 4.0–24.0%).

Conclusions
Medical thoracoscopy is effective and safe when prescribed for complicated parapneumonic effusions and empyema. Bacteriological negativity of pleural effusion specimens and administration of adjuvant intra-pleural fibrinolysis after the procedure are associated with a higher success rate.