bluuebunny/crossref_metadata_2025_split huggingface dataset:
PINNet: a deep neural network with pathway prior knowledge for Alzheimer's disease
Authors: Kim Yeojin , Lee Hyunju 
Published: July 2023

IntroductionIdentification of Alzheimer's Disease (AD)-related transcriptomic signatures from blood is important for early diagnosis of the disease. Deep learning techniques are potent classifiers for AD diagnosis, but most have been unable to identify biomarkers because of their lack of interpretability.MethodsTo address these challenges, we propose a pathway information-based neural network (PINNet) to predict AD patients and analyze blood and brain transcriptomic signatures using an interpretable deep learning model. PINNet is a deep neural network (DNN) model with pathway prior knowledge from either the Gene Ontology or Kyoto Encyclopedia of Genes and Genomes databases. Then, a backpropagation-based model interpretation method was applied to reveal essential pathways and genes for predicting AD.ResultsThe performance of PINNet was compared with a DNN model without a pathway. Performances of PINNet outperformed or were similar to those of DNN without a pathway using blood and brain gene expressions, respectively. Moreover, PINNet considers more AD-related genes as essential features than DNN without a pathway in the learning process. Pathway analysis of protein-protein interaction modules of highly contributed genes showed that AD-related genes in blood were enriched with cell migration, PI3K-Akt, MAPK signaling, and apoptosis in blood. The pathways enriched in the brain module included cell migration, PI3K-Akt, MAPK signaling, apoptosis, protein ubiquitination, and t-cell activation.DiscussionBy integrating prior knowledge about pathways, PINNet can reveal essential pathways related to AD. The source codes are available at https://github.com/DMCB-GIST/PINNet.
Online detection of compensatory strategies in human movement with supervised classification: a pilot study
Authors: Das Neha , Endo Satoshi , Patel Sabrina , Krewer Carmen , Hirche Sandra 
Published: July 2023

IntroductionStroke survivors often compensate for the loss of motor function in their distal joints by altered use of more proximal joints and body segments. Since this can be detrimental to the rehabilitation process in the long-term, it is imperative that such movements are indicated to the patients and their caregiver. This is a difficult task since compensation strategies are varied and multi-faceted. Recent works that have focused on supervised machine learning methods for compensation detection often require a large training dataset of motions with compensation location annotations for each time-step of the recorded motion. In contrast, this study proposed a novel approach that learned a linear classifier from energy-based features to discriminate between healthy and compensatory movements and identify the compensating joints without the need for dense and explicit annotations.MethodsSix healthy physiotherapists performed five different tasks using healthy movements and acted compensations. The resulting motion capture data was transformed into joint kinematic and dynamic trajectories. Inspired by works in bio-mechanics, energy-based features were extracted from this dataset. Support vector machine (SVM) and logistic regression (LR) algorithms were then applied for detection of compensatory movements. For compensating joint identification, an additional condition enforcing the independence of the feature calculation for each observable degree of freedom was imposed.ResultsUsing leave-one-out cross validation, low values of mean brier score (&lt;0.15), mis-classification rate (&lt;0.2) and false discovery rate (&lt;0.2) were obtained for both SVM and LR classifiers. These methods were found to outperform deep learning classifiers that did not use energy-based features. Additionally, online classification performance by our methods were also shown to outperform deep learning baselines. Furthermore, qualitative results obtained from the compensation joint identification experiment indicated that the method could successfully identify compensating joints.DiscussionResults from this study indicated that including prior bio-mechanical information in the form of energy based features can improve classification performance even when linear classifiers are used, both for offline and online classification. Furthermore, evaluation compensation joint identification algorithm indicated that it could potentially provide a straightforward and interpretable way of identifying compensating joints, as well as the degree of compensation being performed.
Identifying risk factors for in-stent restenosis in symptomatic intracranial atherosclerotic stenosis: a systematic review and meta-analysis
Authors: Wang Ning , Lu Yuning , Feng Lei , Lin Dongdong , Gao Yuhai , Wu Jiong , Wang Ming , Wan Shu 
Published: July 2023

BackgroundIn-stent restenosis (ISR) is an adverse and notable event in the treatment of intracranial atherosclerotic stenosis (ICAS) with percutaneous transluminal angioplasty and stenting (PTAS). The incidence and contributing factors have not been fully defined. This study was performed to evaluate factors associated with ISR after PTAS.Data sourceWe identified studies on ISR after PTAS from an electronic search of articles in PubMed, Ovid MEDLINE, and the Cochrane Central Database (dated up to July 2022).ResultsA total of 19 studies, including 452 cases of ISR after 2,047 PTAS, were included in the meta-analysis. The pooled incidence rate of in-stent restenosis was 22.08%. ISR was more likely to occur in patients with coronary artery disease (OR = 1.686; 95% CI: 1.242–2.288; p = 0.0008), dissection (OR = 6.293; 95% CI: 3.883–10.197; p &lt; 0.0001), and higher residual stenosis (WMD = 3.227; 95% CI: 0.142–6.311; p = 0.0404). Patients treated with Wingspan stents had a significantly higher ISR rate than those treated with Enterprise stents (29.78% vs. 14.83%; p &lt; 0.0001).ConclusionsThe present study provides the current estimates of the robust effects of some risk factors for in-stent restenosis in intracranial atherosclerotic stenosis. The Enterprise stent had advantages compared with the Wingspan stent for ISR. The significant risk factors for ISR were coronary artery disease, dissection, and high residual stenosis. Local anesthesia was a suspected factor associated with ISR.
Case report: Expanding the phenotype of FOXP1-related intellectual disability syndrome and hyperkinetic movement disorder in differential diagnosis with epileptic seizures
Authors: Cesaroni Carlo Alberto , Pollazzon Marzia , Mancini Cecilia , Rizzi Susanna , Cappelletti Camilla , Pizzi Simone , Frattini Daniele , Spagnoli Carlotta , Caraffi Stefano Giuseppe , Zuntini Roberta , Trimarchi Gabriele , Niceta Marcello , Radio Francesca Clementina , Tartaglia Marco , Garavelli Livia , Fusco Carlo 
Published: July 2023

ObjectiveWe aimed to report on previously unappreciated clinical features associated with FOXP1-related intellectual disability (ID) syndrome, a rare neurodevelopmental disorder characterized by global developmental delay, intellectual disability, and language delay, with or without autistic features.MethodsWe performed whole-exome sequencing (WES) to molecularly characterize an individual presenting with ID, epilepsy, autism spectrum disorder, behavioral problems, and facial dysmorphisms as major features.ResultsWES allowed us to identify a previously unreported de novo splice site variant, c.1429-1G&gt;T (NM_032682.6), in the FOXP1 gene (OMIM*605515) as the causative event underlying the phenotype. Clinical reassessment of the patient and revision of the literature allowed us to refine the phenotype associated with FOXP1 haploinsufficiency, including hyperkinetic movement disorder and flat angiomas as associated features. Interestingly, the patient also has an asymmetric face and choanal atresia and a novel de novo variant of the CHD7 gene.ConclusionWe suggest that FOXP1-related ID syndrome may also predispose to the development of hyperkinetic movement disorders and flat angiomas. These features could therefore require specific management of this condition.
Listening efficiency in adult cochlear-implant users compared with normally-hearing controls at ecologically relevant signal-to-noise ratios
Authors: Perea Pérez Francisca , Hartley Douglas E. H. , Kitterick Pádraig T. , Zekveld Adriana A. , Naylor Graham , Wiggins Ian M. 
Published: July 2023

IntroductionDue to having to work with an impoverished auditory signal, cochlear-implant (CI) users may experience reduced speech intelligibility and/or increased listening effort in real-world listening situations, compared to their normally-hearing (NH) peers. These two challenges to perception may be usefully integrated in a measure of listening efficiency: conceptually, the amount of accuracy achieved for a certain amount of effort expended.MethodsWe describe a novel approach to quantifying listening efficiency based on the rate of evidence accumulation toward a correct response in a linear ballistic accumulator (LBA) model of choice decision-making. Estimation of this objective measure within a hierarchical Bayesian framework confers further benefits, including full quantification of uncertainty in parameter estimates. We applied this approach to examine the speech-in-noise performance of a group of 24 CI users (M age: 60.3, range: 20–84 years) and a group of 25 approximately age-matched NH controls (M age: 55.8, range: 20–79 years). In a laboratory experiment, participants listened to reverberant target sentences in cafeteria noise at ecologically relevant signal-to-noise ratios (SNRs) of +20, +10, and +4 dB SNR. Individual differences in cognition and self-reported listening experiences were also characterised by means of cognitive tests and hearing questionnaires.ResultsAt the group level, the CI group showed much lower listening efficiency than the NH group, even in favourable acoustic conditions. At the individual level, within the CI group (but not the NH group), higher listening efficiency was associated with better cognition (i.e., working-memory and linguistic-closure) and with more positive self-reported listening experiences, both in the laboratory and in daily life.DiscussionWe argue that listening efficiency, measured using the approach described here, is: (i) conceptually well-motivated, in that it is theoretically impervious to differences in how individuals approach the speed-accuracy trade-off that is inherent to all perceptual decision making; and (ii) of practical utility, in that it is sensitive to differences in task demand, and to differences between groups, even when speech intelligibility remains at or near ceiling level. Further research is needed to explore the sensitivity and practical utility of this metric across diverse listening situations.
Obstructive sleep apnea event detection using explainable deep learning models for a portable monitor
Authors: Alarcón Ángel Serrano , Madrid Natividad Martínez , Seepold Ralf , Ortega Juan Antonio 
Published: July 2023

BackgroundPolysomnography (PSG) is the gold standard for detecting obstructive sleep apnea (OSA). However, this technique has many disadvantages when using it outside the hospital or for daily use. Portable monitors (PMs) aim to streamline the OSA detection process through deep learning (DL).Materials and methodsWe studied how to detect OSA events and calculate the apnea-hypopnea index (AHI) by using deep learning models that aim to be implemented on PMs. Several deep learning models are presented after being trained on polysomnography data from the National Sleep Research Resource (NSRR) repository. The best hyperparameters for the DL architecture are presented. In addition, emphasis is focused on model explainability techniques, concretely on Gradient-weighted Class Activation Mapping (Grad-CAM).ResultsThe results for the best DL model are presented and analyzed. The interpretability of the DL model is also analyzed by studying the regions of the signals that are most relevant for the model to make the decision. The model that yields the best result is a one-dimensional convolutional neural network (1D-CNN) with 84.3% accuracy.ConclusionThe use of PMs using machine learning techniques for detecting OSA events still has a long way to go. However, our method for developing explainable DL models demonstrates that PMs appear to be a promising alternative to PSG in the future for the detection of obstructive apnea events and the automatic calculation of AHI.
Abnormal spontaneous brain activity in females with autism spectrum disorders
Authors: Xie Jiapei , Zhang Weidong , Shen Yu , Wei Wei , Bai Yan , Zhang Ge , Meng Nan , Yue Xipeng , Wang Xinhui , Zhang Xianchang , Wang Meiyun 
Published: July 2023

ObjectivesTo date, most studies on autism spectrum disorder (ASD) have focused on sample sets that were primarily or entirely composed of males; brain spontaneous activity changes in females remain unclear. The purpose of this study was to explore changes in the brain spontaneous neural activity in females with ASD.MethodsIn this study, resting-state functional magnetic resonance images (rs-fMRI) of 41 females with ASD and 41 typically developing (TD) controls were obtained from the ABDIE database. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) of the two groups were calculated to detect the regional brain activity. A two independent sample t-test was used to analyze differences between the ASD and TD groups and a p-value &lt;0.05 was considered statistically significant after false discovery rate (FDR) correction. Pearson correlation analysis was conducted between social responsiveness scale (SRS) scores and the local activity of significantly different brain regions.ResultsCompared with the typically developing (TD) group, the values of ALFF and ReHo were significantly increased in the left superior temporal gyrus (STG), while the values of ReHo were significantly decreased in the left superior frontal gyrus (SFG), left middle occipital gyrus (MOG), bilateral superior parietal lobule (SPL), and bilateral precuneus in the females with ASD group. Correlation analysis showed that the ReHo of the right precuneus was positively correlated to the total SRS, social communication, and autistic mannerisms.ConclusionSpontaneous activity changes in females with ASD involved multiple brain regions and were related to clinical characteristics. Our results may provide some help for further exploring the neurobiological mechanism of females with ASD.
Prevalence and prognostic value of malnutrition in patients with acute coronary syndrome and chronic kidney disease
Authors: Ni Weicheng , Guo Kun , Shi Sanling , Cheng Ling , Zhou Yimin , Zhang Fengyu , Xu Jiachen , Lin Ken , Chen Changxi , Gao Zhan , Zhou Hao 
Published: July 2023

BackgroundMalnutrition is a rising global health issue associated with unfavorable outcomes of a variety of disorders. Currently, the prevalence and prognostic significance of malnutrition to patients with acute coronary syndrome (ACS) and chronic kidney disease (CKD) remained largely unclear.MethodsA total of 705 patients diagnosed with ACS and CKD in the First Affiliated Hospital of Wenzhou Medical University between 2013 and 2021 were included in this retrospective cohort study. Malnutrition was assessed by the Controlling Nutritional Status (CONUT), the Geriatric Nutritional Risk Index (GNRI), and the Prognostic Nutritional Index (PNI), respectively. The relationships between malnutrition and all-cause mortality and major cardiovascular events (MACEs) were analyzed.ResultsDuring a median follow-up of 31 months, 153 (21.7%) patients died, and 165 (23.4%) had MACEs. The prevalence of malnutrition was 29.8, 80.6, and 89.8% for the PNI, CONUT, and GNRI, respectively. All the malnutrition indexes were correlated with each other (r = 0.77 between GNRI and PNI, r = −0.72 between GNRI and CONUT, and r = −0.88 between PNI and CONUT, all p &lt; 0.001). Compared with normal nutrition, malnutrition was independently associated with an increased risk for all-cause mortality (adjusted hazard ratio for moderate and severe degrees of malnutrition, respectively: 7.23 [95% confidence interval (CI): 2.69 to 19.49] and 17.56 [95% CI: 5.61 to 55.09] for the CONUT score, 2.18 [95% CI: 0.93 to 5.13] and 3.16 [95% CI: 1.28 to 7.79] for the GNRI, and 2.52 [95% CI: 1.62 to 3.94] and 3.46 [95% CI: 2.28 to 5.25] for the PNI score. p values were lower than 0.05 for all nutritional indexes, except for moderate GNRI p value = 0.075). As for MACEs, similar results were observed in the CONUT and PNI. All the risk scores could improve the predictive ability of the Global Registry of Acute Coronary Events (GRACE) risk score for both all-cause mortality and MACEs.ConclusionMalnutrition was common in patients with ACS and CKD regardless of the screening tools used, and was independently associated with all-cause mortality and MACEs. Malnutrition scores could facilitate risk stratification and prognosis assessment.
Prognostic value of [18F]-FDG PET/CT in patients with meta-static breast cancer treated with cyclin-dependent inhibitors
Authors: Annovazzi Alessio , Rea Sandra , Maccora Daria , Pizzuti Laura , Ferretti Gianluigi , Vici Patrizia , Cappuzzo Federico , Sciuto Rosa 
Published: July 2023

ObjectiveThe addition of cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) to endocrine therapy impressively improved the outcome of patients with hormone receptor-positive metastatic breast cancer. Despite their great efficacy, not all patients respond to treatment and many of them develop acquired resistance. The aim of this retrospective study was to assess the role of [18F]-FDG PET/CT in predicting PFS and OS in breast cancer patients treated with CDK4/6i.Methods114 patients who performed an [18F]-FDG PET/CT scan before (PET1) and 2-6 months (PET2) after starting treatment were retrospectively enrolled. Metabolic response was evaluated by EORTC, PERCIST and Deauville Score and correlated to PFS and OS.ResultsIn patients who did not progress at PET2 (n = 90), PFS rates were not significantly different between classes of response by EORTC and PERCIST. Conversely, patients showing a Deauville score ≤3 had a longer PFS (median PFS 42 vs 21.0 months; p = 0.008). A higher total metabolic tumor volume at PET1 (TMTV1) was also associated with a shorter PFS (median 18 vs 42 months; p = 0.0026). TMTV1 and Deauville score were the only independent prognostic factors for PFS at multivariate analysis and their combination stratified the population in four definite classes of relapse risk. Conversely, the above parameters did not affect OS which was only influenced by a progressive metabolic disease at PET2 (3-years survival rate 29.8 vs 84.9%; p&lt;0.0001).ConclusionTMTV and metabolic response by Deauville score were significant prognostic factors for PFS in patients with breast cancer treated with CDK4/6i. Their determination could help physicians to select patients who may need a closer follow up.
Same-day versus delayed simulation imaging after placement of a perirectal hydrogel spacer for prostate radiotherapy
Authors: Fredman Elisha , Weinstock-Sabbah Miriam , Icht Oded , Moore Assaf , Shochet Tzippora , Limon Dror , Bragilovski Dimitri 
Published: July 2023

IntroductionPlacement of a perirectal hydrogel spacer has been demonstrated to reduce the risk of rectal toxicity from prostate radiation. Practices vary regarding the timing of CT simulation after hydrogel placement, and the ideal schedule remains unknown.MethodsThirty patients with localized prostate adenocarcinoma underwent transrectal ultrasound-guided placement of an iodinated SpaceOAR™ hydrogel prior to radiotherapy. Per evolving practice, 15 completed same-day simulation and 15 returned for simulation 1–2 weeks later. Hydrogel volume, perirectal distance, air-void volume, and rectal dosimetry per NRG GU005 were compared between CT simulation, 1st fraction Cone-Beam-CT (CBCT), and final CBCT.ResultsCT simulation occurred 8.8 ± 2.4 days after placement in the delayed group, with no significant difference in the interval between simulation and 1st fraction between groups (p = 0.165). Greater observed de-creases in hydrogel volume (0.57 cc vs. 0.04 cc, p = 0.0002), and perirectal distance at both mid-gland (1.32 mm vs. 0.17 mm) and tallest point (2.40 mm vs. 0.04 mm) were seen on 1st-fraction CBCT in the same-day group (p = 0.0039; p = 0.0002). Per dosimetry recalculated on 1st fraction CBCT, five (D3 cc and D50%) versus one (D50%) rectal dose parameters were exceeded in the same-day and delayed groups, respectively, and 10 versus one parameters had a relative increase of ≥ 20%.ConclusionDue to the evolving anatomic changes in the days following hydrogel placement, same-day simulation scanning may introduce unintended variability in rectal dosimetry at the time of prostate radiotherapy.
Impact of RSV test positivity, patient characteristics, and treatment characteristics on the cost of hospitalization for acute bronchiolitis in a French university medical center (2010–2015)
Authors: Dervaux Benoit , Van Berleere Marine , Lenne Xavier , Wyckaert Marine , Dubos François 
Published: July 2023

BackgroundIn young children, respiratory syncytial virus (RSV)-related bronchiolitis is typically more severe than other respiratory tract infections, with a greater need for oxygen therapy and respiratory support. Few studies have compared the cost of hospitalization with regard to virological status. The objective of this study was to compare the costs of hospitalization for RSV-positive vs. RSV-negative bronchiolitis in a French university medical center between 2010 and 2015.MethodsThe cost models were compared using conventional goodness-of-fit criteria. Covariates included the characteristics of the patients, pre-existing respiratory and non-respiratory comorbidities, superinfections, medical care provided, and the length of stay.ResultsRSV was detected in 679 (58.3%) of the 1,164 hospital stays by children under 2 years with virological data. Oxygen therapy and respiratory support were twice as frequent for the RSV-positive cases. The median hospitalization cost was estimated at €3,248.4 (interquartile range: €2,572.1). The cost distribution was positively skewed with a variation coefficient (CV = standard deviation/mean) greater than one (mean = €4,212.9, standard deviation = €5,047, CV = 1.2). In univariate analyses, there was no significant cost difference between the RSV-positive and RSV-negative cases. In the best multivariate model, the significant positive effect of RSV positivity on cost waned after the introduction of medical care variables and the length of stay. The results were sensitive to the specification of the model.ConclusionsIt was impossible to firmly conclude that hospitalization costs were higher for the RSV-positive cases.