bluuebunny/crossref_metadata_2025_split huggingface dataset:
Radiomics-based machine learning analysis and characterization of breast lesions with multiparametric diffusion-weighted MR
Authors: Sun Kun , Jiao Zhicheng , Zhu Hong , Chai Weimin , Yan Xu , Fu Caixia , Cheng Jie-Zhi , Yan Fuhua , Shen Dinggang 
Published: October 2021

Abstract
Background
This study aimed to evaluate the utility of radiomics-based machine learning analysis with multiparametric DWI and to compare the diagnostic performance of radiomics features and mean diffusion metrics in the characterization of breast lesions.

Methods
This retrospective study included 542 lesions from February 2018 to November 2018. One hundred radiomics features were computed from mono-exponential (ME), biexponential (BE), stretched exponential (SE), and diffusion-kurtosis imaging (DKI). Radiomics-based analysis was performed by comparing four classifiers, including random forest (RF), principal component analysis (PCA), L1 regularization (L1R), and support vector machine (SVM). These four classifiers were trained on a training set with 271 patients via ten-fold cross-validation and tested on an independent testing set with 271 patients. The diagnostic performance of the mean diffusion metrics of ME (mADCall b, mADC0–1000), BE (mD, mD*, mf), SE (mDDC, mα), and DKI (mK, mD) were also calculated for comparison. The area under the receiver operating characteristic curve (AUC) was used to compare the diagnostic performance.

Results
RF attained higher AUCs than L1R, PCA and SVM. The AUCs of radiomics features for the differential diagnosis of breast lesions ranged from 0.80 (BE_D*) to 0.85 (BE_D). The AUCs of the mean diffusion metrics ranged from 0.54 (BE_mf) to 0.79 (ME_mADC0–1000). There were significant differences in the AUCs between the mean values of all diffusion metrics and radiomics features of AUCs (all P < 0.001) for the differentiation of benign and malignant breast lesions. Of the radiomics features computed, the most important sequence was BE_D (AUC: 0.85), and the most important feature was FO-10 percentile (Feature Importance: 0.04).

Conclusions
The radiomics-based analysis of multiparametric DWI by RF enables better differentiation of benign and malignant breast lesions than the mean diffusion metrics.
Hydroxyapatite/collagen composite graft for posterior lumbar interbody fusion: a comparison with local bone graft
Authors: Yoshii Toshitaka , Hashimoto Motonori , Egawa Satoru , Hirai Takashi , Inose Hiroyuki , Okawa Atsushi 
Published: October 2021

AbstractBackgroundAutologous bone has been used for posterior lumbar intervertebral fusion (PLIF). However, harvesting autologous bone graft is associated with donor site complications. We previously developed a hydroxyapatite/collagen (HAp/Col) composite as an osteoconductive artificial bone, characterized by having a highly porous structure with sponge‐like elasticity. This study aims to investigate the effectiveness of HAp/Col composite with bone marrow aspirate (BMA) as a graft substitute in PLIF for the treatment of lumbar spinal diseases.MethodsThis study prospectively investigated patients who received one-level PLIF. For the interbody fusion, two titanium cages were inserted. On the one side of interbody space, HAp/Col composite incorporated with BMA filling the titanium cage was grafted. On the other side, local bone graft (LBG) harvested during decompressive laminotomy was grafted and then one-level instrumentation using pedicle screws was performed. The target levels were at L2/3 in 2 cases, L3/4 in 3 cases, L4/5 in 36 cases, and L5/S in 5 cases. We evaluated clinical symptoms and radiological outcomes of 46 patients and compared the fusion status of HAp/Col composite with that of LBG.ResultsThe 1-year postoperative CT evaluation demonstrated that, in the HAp/Col, a complete fusion was observed in 38 patients (82.6%), whereas in the LBG, a complete fusion was observed in 35 patients (76.1%). There were no statistical differences between the HAp/Col and LBG. In the HAp/Col, incomplete fusion was observed in five patients (10.9%) and non-fusion in two patients (4.3%), and in the LBG, incomplete fusion was observed in nine patients (19.6%) and non-fusion in two patients (4.3%). At 2 years after the surgery, complete fusion increased to 44 patients (95.7%) in the HAp/Col and 41 patients (89.1%) in the LBG. There were no significant differences in the clinical scores for lumbar spine between patients with fusion and non-fusion.ConclusionsThe HAp/Col composite with BMA in the titanium cage can be effectively used as an alternative to conventional autologous LBG for intervertebral spinal fusion.Trial registrationUniversity hospital Medical Information Network, UMIN000045010, July 30th, 2021, Retrospectively registered,https://www.umin.ac.jp/english/.
Multivariate data analysis identifies natural clusters of Tuberous Sclerosis Complex Associated Neuropsychiatric Disorders (TAND)
Authors: de Vries Petrus J. , Leclezio Loren , Gardner-Lubbe Sugnet , Krueger Darcy , Sahin Mustafa , Sparagana Steven , De Waele Liesbeth , Jansen Anna 
Published: October 2021

Abstract
Background
Tuberous Sclerosis Complex (TSC), a multi-system genetic disorder, is associated with a wide range of TSC-Associated Neuropsychiatric Disorders (TAND). Individuals have apparently unique TAND profiles, challenging diagnosis, psycho-education, and intervention planning. We proposed that identification of natural TAND clusters could lead to personalized identification and treatment of TAND. Two small-scale studies showed cluster and factor analysis could identify clinically meaningful natural TAND clusters. Here we set out to identify definitive natural TAND clusters in a large, international dataset.

Method
Cross-sectional, anonymized TAND Checklist data of 453 individuals with TSC were collected from six international sites. Data-driven methods were used to identify natural TAND clusters. Mean squared contingency coefficients were calculated to produce a correlation matrix, and various cluster analyses and exploratory factor analysis were examined. Statistical robustness of clusters was evaluated with 1000-fold bootstrapping, and internal consistency calculated with Cronbach’s alpha.

Results
Ward’s method rendered seven natural TAND clusters with good robustness on bootstrapping. Cluster analysis showed significant convergence with an exploratory factor analysis solution, and, with the exception of one cluster, internal consistency of the emerging clusters was good to excellent. Clusters showed good clinical face validity.

Conclusions
Our findings identified a data-driven set of natural TAND clusters from within highly variable TAND Checklist data. The seven natural TAND clusters could be used to train families and professionals and to develop tailored approaches to identification and treatment of TAND. Natural TAND clusters may also have differential aetiological underpinnings and responses to molecular and other treatments.
Clinical spectrum and risk factors for mortality among seawater and freshwater critically ill drowning patients: a French multicenter study
Authors: Reizine Florian , Delbove Agathe , Dos Santos Alexandre , Bodenes Laetitia , Bouju Pierre , Fillâtre Pierre , Frérou Aurélien , Halley Guillaume , Lesieur Olivier , Jonas Maud , Berteau Florian , Morin Jean , Luque-Paz David , Marnai Rémy , Le Meur Anthony , Aubron Cécile , Reignier Jean , Tadié Jean-Marc , Gacouin Arnaud 
Published: October 2021

Abstract
Background
Drowning is a global threat and one of the leading causes of injury around the world. The impact of drowning conditions including water salinity on patients’ prognosis remains poorly explored in Intensive Care Units (ICUs) patients.

Methods
We conducted a retrospective multicenter study on patients admitted to 14 ICUs in the west of France from January 2013 to January 2020. We first compared demographic and clinical characteristics at admission as well as clinical courses of these patients according to the salinity of drowning water. Then, we aimed to identify variables associated with 28-day survival using a Cox proportional hazard model.

Results
Of the 270 consecutive included patients, drowning occurred in seawater in 199 patients (73.7%) and in freshwater in 71 patients (26.3%). Day-28 mortality was observed in 55 patients (20.4%). Freshwater was independently associated with 28-day mortality (Adjusted Hazard Ratio (aHR) 1.84 [95% Confidence Interval (CI) 1.03–3.29], p = 0.04). A higher proportion of freshwater patients presented psychiatric comorbidities (47.9 vs. 19.1%; p < 0.0001) and the etiology of drowning appeared more frequently to be a suicide attempt in this population (25.7 vs. 4.2%; p < 0.0001). The other factors independently associated with 28-day mortality were the occurrence of a drowning-related cardiac arrest (aHR 11.5 [95% CI 2.51–52.43], p = 0.0017), duration of cardiopulmonary resuscitation (aHR 1.05 [95% CI 1.03–1.07], p < 0.0001) and SOFA score at day 1 (aHR 1.2 [95% CI 1.11–1.3], p < 0.0001).

Conclusions
In this large multicenter cohort, freshwater drowning patients had a poorer prognosis than saltwater drowning patients. Reasons for such discrepancies include differences in underlying psychiatric comorbidity, drowning circumstances and severities. Patients with initial cardiac arrest secondary to drowning remain with a very poor prognosis.
Advancing motor rehabilitation for adults with chronic neurological conditions through increased involvement of kinesiologists: a perspective review
Authors: Mang Cameron S. , Peters Sue 
Published: October 2021

AbstractMany people with neurological conditions experience challenges with movement. Although rehabilitation is often provided acutely and sub-acutely following the onset of a condition, motor deficits commonly persist in the long-term and are exacerbated by disuse and inactivity. Notably, motor rehabilitation approaches that incorporate exercise and physical activity can support gains in motor function even in the chronic stages of many neurological conditions. However, delivering motor rehabilitation on a long-term basis to people with chronic neurological conditions is a challenge within health care systems, and the onus is often placed on patients to find and pay for services. While neurological motor rehabilitation is largely the domain of physical and occupational therapists, kinesiologists may be able to complement existing care and support delivery of long-term neurological motor rehabilitation, specifically through provision of supported exercise and physical activity programs. In this perspective style review article, we discuss potential contributions of kinesiologists to advancing the field through exercise programming, focusing on community-based interventions that increase physical activity levels. We conclude with recommendations on how kinesiologists’ role might be further optimized towards improving long-term outcomes for people with chronic neurological conditions, considering issues related to professional regulation and models of care.
Repeatability of methylation measures using a QIAseq targeted methyl panel and comparison with the Illumina HumanMethylation450 assay
Authors: Yu Chenglong , Dugué Pierre-Antoine , Dowty James G. , Hammet Fleur , Joo JiHoon E. , Wong Ee Ming , Hosseinpour Mahnaz , Giles Graham G. , Hopper John L. , Nguyen-Dumont Tu , MacInnis Robert J. , Southey Melissa C. 
Published: October 2021

Abstract
Objective
In previous studies using Illumina Infinium methylation arrays, we have identified DNA methylation marks associated with cancer predisposition and progression. In the present study, we have sought to find appropriate technology to both technically validate our data and expand our understanding of DNA methylation in these genomic regions. Here, we aimed to assess the repeatability of methylation measures made using QIAseq targeted methyl panel and to compare them with those obtained from the Illumina HumanMethylation450 (HM450K) assay. We included in the analysis high molecular weight DNA extracted from whole blood (WB) and DNA extracted from formalin-fixed paraffin-embedded tissues (FFPE).

Results
The repeatability of QIAseq-methylation measures was assessed at 40 CpGs, using the Intraclass Correlation Coefficient (ICC). The mean ICCs and 95% confidence intervals (CI) were 0.72 (0.62–0.81), 0.59 (0.47–0.71) and 0.80 (0.73–0.88) for WB, FFPE and both sample types combined, respectively. For technical replicates measured using QIAseq and HM450K, the mean ICCs (95% CI) were 0.53 (0.39–0.68), 0.43 (0.31–0.56) and 0.70 (0.59–0.80), respectively. Bland–Altman plots indicated good agreement between QIAseq and HM450K measurements. These results demonstrate that the QIAseq targeted methyl panel produces reliable and reproducible methylation measurements across the 40 CpGs that were examined.
The impact of near visual impairment on instrumental activities of daily living among community-dwelling older adults in Selangor
Authors: Kee Qiu Ting , Abd Rahman Mohd Harimi , Mohamad Fadzil Norliza , Mohammed Zainora , Shahar Suzana 
Published: October 2021

Abstract
Objective
Near visual impairment (VI) is a common disability in an aging population. Near vision is crucial in activity of daily living including reading, smartphone and computer use and meal preparation. This study was conducted to determine the association between near visual acuity (VA) and contrast sensitivity (CS) with activity of daily living (ADL) among visually impaired older adults.

Results
A total of 208 participants aged  ≥  60 were recruited from the population-based longitudinal study on neuroprotective model for healthy longevity. Habitual near VA and CS were measured using Lighthouse near VA chart and Pelli-Robson CS chart, respectively. Lawton instrumental activities of daily living (IADL) was used to assess ADL. There are 41.8% participants with near visual impairment and 28.7% among them had IADL disability. Independent t test showed significant lower mean IADL score among visually impaired participants [t(206)  =  2.03, p  =  0.04]. IADL score significantly correlated with near VA (r  =   − 0.21, p  =  0.05) but not with CS (r  =   − 0.14, p = 0.21). Near VA (B  =   − 0.44, p  =  0.03) and age (B  =   − 0.07, p  =  0.01) significantly predicted IADL. The findings show poorer VA renders higher IADL disability, which may necessitate interventions to improve ADL among visually impaired older adults.
Costs incurred by patients with oral potentially malignant disorders: is there a public health need for financial protection in India?
Authors: Patel Jay R. , Rupani Mihir P. 
Published: October 2021

Abstract
Objectives
Financial protection mechanisms are in place to overcome the costs of a few diseases in India. Our objective was to estimate the costs incurred due to Oral Potentially Malignant Disorders (OPMD) and to determine predictors of such costs.

Results
We found that the median (Interquartile range IQR) total costs of OPMD was Indian Rupees (INR) 500 (350–750), direct medical costs was INR 0 (0–50), direct non-medical costs was INR 150 (40–200) and indirect costs was INR 350 (250–500). The travel cost to attend the health facilities [INR 100 (40–150)] and the patient’s loss of wages [INR 200 (150–400)] mainly accounted for the direct non-medical and indirect costs respectively. The median expenditure on smokeless and smoking forms of tobacco was INR 6000 (5400–7200) and INR 2400 (1800–3600) respectively. On multiple linear regression analysis, rural residence, belonging to below poverty line family, being a sole earner in the family, number of months since diagnosis and first visit at a private provider were found to be the significant predictors of total costs of OPMD. Financial protection mechanisms are needed for covering the direct non-medical and indirect costs. Early management of OPMD might mitigate the costs of OPMD.
Multi-target vital signs detection using frequency-modulated continuous wave radar
Authors: Wang Yong , Shui Yuzhu , Yang Xiaobo , Li Zhaoyu , Wang Wen 
Published: October 2021

AbstractRespiration and heartbeats rates are important physiological assessment indicators that provide valid prior-knowledge for the diagnosis of numerous diseases. However, most of the current research focuses on the vital signs measurement of single target, and multi-target vital signs detection has not received much attention. In this paper, we use frequency-modulated continuous wave (FMCW) radar to measure the vital signs signals of multi-target. First, we apply the three-dimensional fast Fourier transform (3D-FFT) method to separate multiple targets and get their distance and azimuth information. Subsequently, the linear constrained minimum variance-based adaptive beamforming (LCMV-ADBF) technique is proposed to form a spatially distributed beams on the targets of interest directions. Finally, a compressive sensing based on orthogonal matching pursuit (CS-OMP) method and rigrsure adaptive soft threshold noise reduction based on discrete wavelet transform (RA-DWT) method are present to extract the respiratory and heartbeat signals. We perform tests in a real experimental environment and compare the proposed method with reference devices. The results show that the degrees of agreement for respiratory and heartbeat are 89% and 87%, respectively, for two human targets. The level of agreement for respiratory and heartbeat is 87% and 85%, respectively, for three human targets, proving the effectiveness of the proposed method.
Speech enhancement from fused features based on deep neural network and gated recurrent unit network
Authors: Wang Youming , Han Jiali , Zhang Tianqi , Qing Didi 
Published: October 2021

AbstractSpeech is easily interfered by external environment in reality, which results in the loss of important features. Deep learning has become a popular speech enhancement method because of its superior potential in solving nonlinear mapping problems for complex features. However, the deficiency of traditional deep learning methods is the weak learning capability of important information from previous time steps and long-term event dependencies between the time-series data. To overcome this problem, we propose a novel speech enhancement method based on the fused features of deep neural networks (DNNs) and gated recurrent unit (GRU). The proposed method uses GRU to reduce the number of parameters of DNNs and acquire the context information of the speech, which improves the enhanced speech quality and intelligibility. Firstly, DNN with multiple hidden layers is used to learn the mapping relationship between the logarithmic power spectrum (LPS) features of noisy speech and clean speech. Secondly, the LPS feature of the deep neural network is fused with the noisy speech as the input of GRU network to compensate the missing context information. Finally, GRU network is performed to learn the mapping relationship between LPS features and log power spectrum features of clean speech spectrum. The proposed model is experimentally compared with traditional speech enhancement models, including DNN, CNN, LSTM and GRU. Experimental results demonstrate that the PESQ, SSNR and STOI of the proposed algorithm are improved by 30.72%, 39.84% and 5.53%, respectively, compared with the noise signal under the condition of matched noise. Under the condition of unmatched noise, the PESQ and STOI of the algorithm are improved by 23.8% and 37.36%, respectively. The advantage of the proposed method is that it uses the key information of features to suppress noise in both matched and unmatched noise cases and the proposed method outperforms other common methods in speech enhancement.
Communication energy optimization of electric vehicle platoon on curved road
Authors: Gao Wei , Peng Chunrong , Bao Wugedele , Wu Celimuge 
Published: October 2021

AbstractThe cruising range of an electric vehicle is limited by its battery. Reducing the energy consumption of MES (main energy systems) or AES (auxiliary energy systems) of the vehicle battery is an effective means to increase the electric vehicle cruising range. Platoon driving can greatly reduce the wind resistance of the vehicle and then reduce the energy consumption of MES for electric vehicles. This paper proposes an adaptive communication energy optimization scheme based on road curvature radius to save the energy of AES for the electric vehicle platoon on curved roads. In this paper, the inter-vehicle distance error based on the car-like model in a two-dimensional space is established. Then, the inter-vehicle distance error is used to design a control law K to accomplish successful platooning. Next, three platooning control schemes based on different information flow topologies are discussed. Finally, the consensus of three platooning control schemes and the energy consumption of electric vehicle communication systems are analyzed by MATLAB’s Simulink. Simulation results show that the communication energy optimization scheme reduces the power consumption of AES as long as the platoon driving on curved roads.
Some applications of q-difference operator involving a family of meromorphic harmonic functions
Authors: Khan Neelam , Srivastava H. M. , Rafiq Ayesha , Arif Muhammad , Arjika Sama 
Published: October 2021

AbstractIn this paper, we establish certain new subclasses of meromorphic harmonic functions using the principles ofq-derivative operator. We obtain new criteria of sense preserving and univalency. We also address other important aspects, such as distortion limits, preservation of convolution, and convexity limitations. Additionally, with the help of sufficiency criteria, we estimate sharp bounds of the real parts of the ratios of meromorphic harmonic functions to their sequences of partial sums.
Neurocognitive, psychiatric, and substance use characteristics in a diverse sample of persons with OUD who are starting methadone or buprenorphine/naloxone in opioid treatment programs
Authors: Scott Travis M. , Arnsten Julia , Olsen James Patrick , Arias Franchesca , Cunningham Chinazo O. , Rivera Mindt Monica 
Published: October 2021

Abstract
Background
Medications for opioid use disorder such as opioid agonist treatment (OAT, including methadone, buprenorphine) are the gold standard intervention for opioid use disorder (OUD). Persons with OUD have high rates of neurocognitive impairment and psychiatric and substance use disorders, but few studies have examined these characteristics in diverse patients initiating OAT in opioid treatment programs (OTPs). Additionally, in these individuals, poor neurocognitive functioning and psychiatric/other substance use disorders are associated with poor OUD treatment outcomes. Given rapid changes in the opioid epidemic, we sought to replicate findings from our pilot study by examining these characteristics in a large diverse sample of persons with OUD starting OTP-based OAT.

Methods
Ninety-seven adults with OUD (M age = 42.2 years [SD = 10.3]; M education = 11.4 years [SD = 2.3]; 27% female; 22% non-Hispanic white) were enrolled in a randomized longitudinal trial evaluating methadone versus buprenorphine/naloxone on neurocognitive functioning. All participants completed a comprehensive neurocognitive, psychiatric, and substance use evaluation within one week of initiating OAT.

Results
Most of the sample met criteria for learning (79%) or memory (69%) impairment. Half exhibited symptoms of current depression, and comorbid substance use was highly prevalent. Lifetime cannabis and cocaine use disorders were associated with better neurocognitive functioning, while depression was associated with worse neurocognitive functioning.

Conclusions
Learning and memory impairment are highly prevalent in persons with OUD starting treatment with either methadone or buprenorphine/naloxone in OTPs. Depression and comorbid substance use are prevalent among these individuals, but neither impact learning or memory. However, depression is associated with neurocognitive impairment in other domains. These findings might allow clinicians to help persons with OUD starting OAT to develop compensatory strategies for learning and memory, while providing adjunctive treatment for depression.
Trial Registration NCT, NCT01733693. Registered November 4, 2012, https://clinicaltrials.gov/ct2/show/NCT01733693.