bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrated Analysis of Transcriptomic and Genomic Data Reveals Blood Biomarkers With Diagnostic and Prognostic Potential in Non-small Cell Lung Cancer
Authors: Kaya Ibrahim H. , Al-Harazi Olfat , Kaya Mustafa T. , Colak Dilek 
Published: March 2022

Background: Lung cancer is the second most common cancer and the main leading cause of cancer-associated death worldwide. Non-small cell lung cancer (NSCLC) accounts for about 85% of lung cancer diagnoses and more than 50% of all lung cancer cases are diagnosed at an advanced stage; hence have poor prognosis. Therefore, it is important to diagnose NSCLC patients reliably and as early as possible in order to reduce the risk of mortality.Methods: We identified blood-based gene markers for early NSCLC by performing a multi-omics approach utilizing integrated analysis of global gene expression and copy number alterations of NSCLC patients using array-based techniques. We also validated the diagnostic and the prognostic potential of the gene signature using independent datasets with detailed clinical information.Results: We identified 12 genes that are significantly expressed in NSCLC patients’ blood, at the earliest stages of the disease, and associated with a poor disease outcome. We then validated 12-gene signature’s diagnostic and prognostic value using independent datasets of gene expression profiling of over 1000 NSCLC patients. Indeed, 12-gene signature predicted disease outcome independently of other clinical factors in multivariate regression analysis (HR = 2.64, 95% CI = 1.72–4.07; p = 1.3 × 10−8). Significantly altered functions, pathways, and gene networks revealed alterations in several key genes and cancer-related pathways that may have importance for NSCLC transformation, including FAM83A, ZNF696, UBE2C, RECK, TIMM50, GEMIN7, and XPO5.Conclusion: Our findings suggest that integrated genomic and network analyses may provide a reliable approach to identify genes that are associated with NSCLC, and lead to improved diagnosis detecting the disease in early stages in patients’ blood instead of using invasive techniques and also have prognostic potential for discriminating high-risk patients from the low-risk ones.
Transformer-Based High-Frequency Oscillation Signal Detection on Magnetoencephalography From Epileptic Patients
Authors: Guo Jiayang , Xiao Naian , Li Hailong , He Lili , Li Qiyuan , Wu Ting , He Xiaonan , Chen Peizhi , Chen Duo , Xiang Jing , Peng Xueping 
Published: March 2022

High-frequency oscillations (HFOs), observed within 80–500 Hz of magnetoencephalography (MEG) data, are putative biomarkers to localize epileptogenic zones that are critical for the success of surgical epilepsy treatment. It is crucial to accurately detect HFOs for improving the surgical outcome of patients with epilepsy. However, in clinical practices, detecting HFOs in MEG signals mainly depends on visual inspection by clinicians, which is very time-consuming, labor-intensive, subjective, and error-prone. To accurately and automatically detect HFOs, machine learning approaches have been developed and have demonstrated the promising results of automated HFO detection. More recently, the transformer-based model has attracted wide attention and achieved state-of-the-art performance on many machine learning tasks. In this paper, we are investigating the suitability of transformer-based models on the detection of HFOs. Specifically, we propose a transformer-based HFO detection framework for biomedical MEG one-dimensional signal data. For signal classification, we develop a transformer-based HFO (TransHFO) classification model. Then, we investigate the relationship between depth of deep learning models and classification performance. The experimental results show that the proposed framework outperforms the state-of-the-art HFO classifiers, increasing classification accuracy by 7%. Furthermore, we find that shallow TransHFO (<10 layers) outperforms deep TransHFO models (≥10 layers) on most data augmented factors.
A Comparison of Energy-Efficient Seizure Detectors for Implantable Neurostimulation Devices
Authors: Manzouri Farrokh , Zöllin Marc , Schillinger Simon , Dümpelmann Matthias , Mikut Ralf , Woias Peter , Comella Laura Maria , Schulze-Bonhage Andreas 
Published: March 2022

IntroductionAbout 30% of epilepsy patients are resistant to treatment with antiepileptic drugs, and only a minority of these are surgical candidates. A recent therapeutic approach is the application of electrical stimulation in the early phases of a seizure to interrupt its spread across the brain. To accomplish this, energy-efficient seizure detectors are required that are able to detect a seizure in its early stages.MethodsThree patient-specific, energy-efficient seizure detectors are proposed in this study: (i) random forest (RF); (ii) long short-term memory (LSTM) recurrent neural network (RNN); and (iii) convolutional neural network (CNN). Performance evaluation was based on EEG data (n = 40 patients) derived from a selected set of surface EEG electrodes, which mimic the electrode layout of an implantable neurostimulation system. As for the RF input, 16 features in the time- and frequency-domains were selected. Raw EEG data were used for both CNN and RNN. Energy consumption was estimated by a platform-independent model based on the number of arithmetic operations (AOs) and memory accesses (MAs). To validate the estimated energy consumption, the RNN classifier was implemented on an ultra-low-power microcontroller.ResultsThe RNN seizure detector achieved a slightly better level of performance, with a median area under the precision-recall curve score of 0.49, compared to 0.47 for CNN and 0.46 for RF. In terms of energy consumption, RF was the most efficient algorithm, with a total of 67k AOs and 67k MAs per classification. This was followed by CNN (488k AOs and 963k MAs) and RNN (772k AOs and 978k MAs), whereby MAs contributed more to total energy consumption. Measurements derived from the hardware implementation of the RNN algorithm demonstrated a significant correlation between estimations and actual measurements.DiscussionAll three proposed seizure detection algorithms were shown to be suitable for application in implantable devices. The applied methodology for a platform-independent energy estimation was proven to be accurate by way of hardware implementation of the RNN algorithm. These findings show that seizure detection can be achieved using just a few channels with limited spatial distribution. The methodology proposed in this study can therefore be applied when designing new models for responsive neurostimulation.
Cerebellar and Cerebral Amyloid Visualized by [18F]flutemetamol PET in Long-Term Hereditary V30M (p.V50M) Transthyretin Amyloidosis Survivors
Authors: Uneus Erica Irene , Wilhelmsson Christer , Bäckström David , Anan Intissar , Wixner Jonas , Pilebro Björn , Riklund Katrine , Ögren Mattias , Ögreen Margareta , Axelsson Jan , Suhr Ole B. , Sundström Torbjörn 
Published: March 2022

IntroductionHereditary transthyretin (ATTRv) amyloidosis caused by the V30M (p. V50M) mutation is a fatal, neuropathic systemic amyloidosis. Liver transplantation has prolonged the survival of patients and central nervous system (CNS) complications, attributed to amyloid angiopathy caused by CNS synthesis of variant transthyretin, have emerged. The study aimed to ascertain amyloid deposition within the brain in long-term ATTRv amyloidosis survivors with neurological symptoms from the CNS.MethodsA total of 20 patients with ATTR V30M having symptoms from the CNS and a median disease duration of 16 years (8–25 years) were included in this study. The cognitive and peripheral nervous functions were determined for 18 patients cross-sectionally at the time of the investigation. Amyloid brain deposits were examined by [18F]flutemetamol PET/CT. Five patients with Alzheimer's disease (AD) served as positive controls.Result60% of the patients with ATTRv had a pathological Z-score in the cerebellum, compared to only 20% in the patients with AD. 75% of the patients with transient focal neurological episodes (TFNEs) displayed a pathological uptake only in the cerebellum. Increased cerebellar uptake was related to an early age of onset of the ATTRv disease. 55% of the patients with ATTRv had a pathological Z-score in the global cerebral region compared to 100% of the patients with AD.ConclusionAmyloid deposition within the brain after long-standing ATTRv amyloidosis is common, especially in the cerebellum. A cerebellar amyloid uptake profile seems to be related to TFNE symptoms.
Adherence to the Chinese Food Pagoda in the High-Risk Population of Non-communicable Diseases Aged 35–59 in Central China
Authors: Jiang Qingqing , You Qiqi , Lou Yiling , Wang Shiqi , Cao Shiyi 
Published: March 2022

ObjectivesA healthy dietary habit is essential for preventing non-communicable diseases (NCDs). We aimed to assess the adherence to the Chinese Food Pagoda (CFP) proposed in the Chinese Dietary Guidelines 2016 in the high-risk population of NCDs in central China.MethodsA cross-sectional study was conducted in two large enterprises (totally 3,016 employees) from October to December 2019 in Hubei Province (central China). The high-risk population of NCDs was identified by physical examination, laboratory test and face-to-face questionnaire survey according to the National Norms for Prevention and Control of Non-communicable Diseases issued by the Chinese government. We assessed the deviation of real diet from the CFP recommended diet in the high-risk population of NCDs.ResultsA total of 821 participants aged 35–59 years old with at least one high-risk factor of NCDs were enrolled in our study. Of them, 53.8% were daily smokers, 49.6% had elevated blood cholesterol, 31.4% were centrally obese, 23.3% had high normal blood pressure, and 3.5% had impaired fasting glucose. Significant disparity was detected in the high-risk population of NCDs between real food consumption and the CFP's recommendation (P &lt; 0.05), such as the deficient intake of nuts and milk and dairy products, and the over-consumption of cereals, meat and poultry, oil, and salt. Participants with impaired fasting glucose had the highest intake of cereals and vegetables on average. Participants with central obesity were more likely to consume meat and poultry (P &lt; 0.05). The lowest average intake of eggs and the highest average intake of milk and dairy products were found in participants with high blood cholesterol (P &lt; 0.05). The daily smokers were more likely to consume beans and nuts (P &lt; 0.05). The lowest average intake of fruits and the highest average intake of tubers were found in participants with high normal blood pressure (P &lt; 0.05).ConclusionAdherence to CFP in the high-risk population of NCDs appeared to be challenging. It is necessary to adopt dietary education campaign focusing on the high-risk population of NCDs to prevent or delay the occurrence of NCDs.
Nutrition and Congruent Care Improve Wellbeing of Residents With Dementia in Slovenian Care Homes
Authors: KejŽar Anamarija , Rihter Liljana , Sajovic Jakob , Drevenšek Gorazd 
Published: March 2022

IntroductionCurrent nutritional strategies for people with dementia focus on nutritional diets and regimens, although in recent years congruent care for people with dementia has been increasingly recognized to improve their wellbeing. This includes consistency of care, respecting the variability of psycho-sociological factors, emphasizing the importance of participation in activities, and congruence with the individual's needs and capabilities. When applied to the nutritional aspects of care, it aims to empower people with dementia to have an active role in their care and during meals. Congruent care has previously shown promising results in improving the quality of life of residents, reducing the incidence of negative social interactions and daily intake of medicines.MethodsA mixed methods qualitative-quantitative study was carried out. Out of 102 residential care homes for the elderly in Slovenia, a non-random sample of homes was selected. Seven homes that have implemented congruent care and five who have not implemented it agreed to participate. Content analysis of the transcripts of focus group interviews was carried out, to establish how the congruent care model was included into their everyday practice of care for people with dementia. Qualitative comparative analysis was used to describe the differences in the practice of care between the two groups of homes, in the fields of nutritional and general care. Frequencies and assigned importance of statements relating to different aspects of nutritional care were statistically compared.ResultsThe introduction of congruent care improved the wellbeing of the people with dementia, as observed by caregivers. The homes that had implemented congruent care gave more attention to the food choice aspects of nutritional care (p = 0.0474, 95%CICongruent = 50.77–72.35%, 95%CINon−congruent = 27.65–49.23%), while the homes that had not were more attentive to the dietary intake aspects (p = 0.0067, 95%CICongruent = 22.79–44.74%, 95%CINon−congruent = 55.26–77.21%). In the homes for the elderly that had implemented congruent care, both caregivers and management reported that the frequency of use of pro re nata medication decreased, which is supported by the results of the linear regression (R2adjusted =78.4, p = 0.005), although the data available is limited.ConclusionFirst, the people with dementia in the care homes that had implemented congruent care were observed to have improved in mood, attitudes toward eating and wellbeing, as reported by caregivers. Second, the implementation of congruent care was well received by the management and caregivers of the care homes. A model of implementation of congruent nutritional care for people with dementia is presented.
Benefits of Targeted Molecular Therapy to Immune Infiltration and Immune-Related Genes Predicting Signature in Breast Cancer
Authors: Chen Fahai , Fang Jianmin 
Published: March 2022

BackgroundThis study aimed to investigate the tumor-related infiltrating lymphocytes (TILs) affecting the response of trastuzumab and identify potential biomarkers based on immune-related genes to improve prognosis and clinical outcomes of targeted therapies in breast cancer.MethodsEstimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) was adopted to infer the fraction of stromal and immune cells through utilizing gene expression signatures in breast tumor samples. Cell-type identification by estimating relative subsets of RNA transcript (CIBERSORT) algorithm was applied to characterize cell composition of 22 lymphocytes from breast cancer tissues using their gene expression profiles. Immune-related genes were collected from the Immunology Database and Analysis (ImmPort). Univariate and multivariate Cox regression analyses were performed to identify the significant independent risk factors associated with poor overall survival (OS) and breast cancer-specific survival (BCSS) of breast cancer patients. Hub genes were identified based on the protein–protein interaction (PPI) network analysis.ResultsBased on the ESTIMATE algorithm, a significant reduction of stromal scores was observed in tumor tissues and pretreated tumor tissues compared with nontumor and posttreated tumor tissues, respectively, while immune scores failed to present notably statistical differences between both groups. However, from the results of the univariate Cox regression analysis, the immune score was identified to be remarkably associated with the poor OS for breast cancer patients. Subsequently, the infiltrating lymphocytes were evaluated in tumor tissues based on the CIBERSORT algorithm. Furthermore, significance analysis identified 1,244 differentially expressed genes (DEGs) from the GSE114082 dataset, and then 91 overlapping immune-related DEGs were screened between GSE114082 and ImmPort datasets. Subsequently, 10 top hub genes were identified and five (IGF1, ADIPOQ, PPARG, LEP, and NR3C1) significantly correlated with worse OS and BCSS on response to trastuzumab in breast cancer patients.ConclusionsThis study provided an insight into the immune score based on the tumor-related infiltrating lymphocytes in breast cancer tissues and demonstrates the benefits of immune infiltration on the treatment of trastuzumab. Meanwhile, the study established a novel five immune-related gene signature to predict the OS and BCSS of breast cancer treated by trastuzumab.
Expression of GPR68, an Acid-Sensing Orphan G Protein-Coupled Receptor, in Breast Cancer
Authors: Elemam Noha Mousaad , Youness Rana A. , Hussein Amal , Shihab Israa , Yakout Nada M. , Elwany Yasmine Nagy , Manie Tamer M. , Talaat Iman M. , Maghazachi Azzam A. 
Published: March 2022

BackgroundBreast cancer (BC) is the most diagnosed cancer and the leading cause of global cancer incidence in 2020. It is quite known that highly invasive cancers have disrupted metabolism that leads to the creation of an acidic tumor microenvironment. Among the proton-sensing G protein-coupled receptors is GPR68. In this study, we aimed to explore the expression pattern of GPR68 in tissues from BC patients as well as different BC cell lines. Methods: In-silico tools were used to assess the expression of GPR68 in BC patients. The expression pattern was validated in fresh and paraffin-embedded sections of BC patients using qPCR and immunohistochemistry (IHC), respectively. Also, in-silico tools investigated GPR68 expression in different BC cell lines. Validation of GPR68 expression was performed using qPCR and immunofluorescence techniques in four different BC cell lines (MCF-7, MDA-MB-231, BT-549 and SkBr3). Results: GPR68 expression was found to be significantly increased in BC patients using the in-silico tools and validation using qPCR and IHC. Upon classification according to the molecular subtypes, the luminal subtype showed the highest GPR68 expression followed by triple-negative and Her2-enriched cells. However, upon validation in the recruited cohort, the triple-negative molecular subtype of BC patients showed the highest GPR68 expression. Also, in-silico and validation data revealed that the triple-negative breast cancer cell line MDA-MB-231 showed the highest expression of GPR68. Conclusion: Therefore, this study highlights the potential utilization of GPR68 as a possible diagnostic and/or prognostic marker in BC.
Lynch Syndrome-Associated Endometrial Cancer With Combined EPCAM-MSH2 Deletion: A Case Report
Authors: Huang Rong , Deng Xiangyu , Zhang Zhenhua , Wen Qinglian , Li Dan 
Published: March 2022

BackgroundLynch syndrome (LS), an autosomal dominant disorder, is characterized by germline pathogenic variants in DNA mismatch repair (MMR) genes like MSH2. EPCAM deletions cause a minority (3%) of LS cases. However, there are only a few reports of LS-associated endometrial cancer (LS-EC) induced by the inactivation of the MSH2 gene due to EPCAM deletions.Case PresentationWe present the case of a 45-years old woman diagnosed with endometrial cancer (EC). Definitive surgery revealed meso-differentiated endometrioid adenocarcinoma, stage IA without lymph-vascular space invasion. Four months later, she received radiation therapy (125I radioactive seeds implantation), and platinum-containing regimen combined chemotherapy because of vaginal stump metastasis of EC. After five years, we performed immunohistochemistry (IHC) on pelvic mass because of presacral metastatic lymph node. IHC showed the absence of MSH2 and MSH6 protein expression in the pelvic mass tissue. Peripheral blood was used for genetic testing based on her cancer diagnosis and family history of cancer in close relatives. Genetic testing revealed deletions of exon 8 and 9 in EPCAM and deletions of exon 1 and 8 in MSH2; thus, we diagnosed the presence of LS. The patient underwent interstitial brachytherapy (BT) of the presacral metastatic lymph node.ConclusionThis case highlights that patients with LS-EC who are carriers of combined EPCAM-MSH2 deletion might experience better oncologic outcomes even with early recurrence.
Using Aggregate Vasoactive-Inotrope Scores to Predict Clinical Outcomes in Pediatric Sepsis
Authors: Shah Palak , Petersen Tara L. , Zhang Liyun , Yan Ke , Thompson Nathan E. 
Published: March 2022

ObjectivesThe heterogeneity of sepsis makes it difficult to predict outcomes using existing severity of illness tools. The vasoactive-inotrope score (VIS) is a quantitative measure of the amount of vasoactive support required by patients. We sought to determine if a higher aggregate VIS over the first 96 h of vasoactive medication initiation is associated with increased resource utilization and worsened clinical outcomes in pediatric patients with severe sepsis.DesignRetrospective cohort study.SettingSingle-center at Children's Wisconsin in Milwaukee, WI.PatientsOne hundred ninety-nine pediatric patients, age less than 18 years old, diagnosed with severe sepsis, receiving vasoactive medications between January 2017 and July 2019.InterventionsRetrospective data obtained from the electronic medical record, calculating VIS at 2 h intervals from 0–12 h and at 4 h intervals from 12–96 h from Time 0.MeasurementsAggregate VIS derived from the hourly VIS area under the curve (AUC) calculation based on the trapezoidal rule. Data were analyzed using Pearson's correlations, Mann-Whitney test, Wilcoxon signed rank test, and classification, and regression tree (CART) analyses.Main ResultsHigher aggregate VIS is associated with longer hospital LOS (p &lt; 0.0001), PICU LOS (p &lt; 0.0001), MV days (p = 0.018), increased in-hospital mortality (p &lt; 0.0001), in-hospital cardiac arrest (p = 0.006), need for ECMO (p &lt; 0.0001), and need for CRRT (p &lt; 0.0001). CART analyses found that aggregate VIS &gt;20 is an independent predictor for in-hospital mortality (p &lt; 0.0001) and aggregate VIS &gt;16 for ECMO use (p &lt; 0.0001).ConclusionsThere is a statistically significant association between aggregate VIS and many clinical outcomes, allowing clinicians to utilize aggregate VIS as a physiologic indicator to more accurately predict disease severity/trajectory in pediatric sepsis.
Do GnRH Agonists Really Increase Body Weight Gain? Evaluation of a Multicentric Portuguese Cohort of Patients With Central Precocious Puberty
Authors: Leite Ana Luísa , Galo Elisa , Antunes Ana , Robalo Brígida , Amaral Daniela , Espada Filipa , Castro Sofia , Simões Dias Sara , Limbert Catarina 
Published: March 2022

IntroductionThere are several concerns associated with gonadotropin-releasing hormone agonist (GnRHa) treatment for central precocious puberty (CPP), such as obesity and changes in body mass index (BMI). We aimed to investigate whether any anthropometric differences exist and if they persist over time.MethodsWe conducted an observational study of Portuguese children (both sexes) diagnosed with CPP between January 2000 and December 2017, using a digital platform, in order to analyze the influence of GnRHa treatment on BMI-SD score (BMI-SDS).ResultsOf the 241 patients diagnosed with CPP, we assessed 92 patients (8% boys) in this study. At baseline, 39% of the patients were overweight. BMI-SDS increased with treatment for girls but then diminished 1 year after stopping GnRHa therapy (p = 0.018). BMI-SDS variation at the end of treatment was negatively correlated with BMI-SDS at baseline (p &lt; 0.001). Boys grew taller and faster during treatment than did girls (p &lt; 0.001), and therefore, their BMI-SDS trajectory might be different.ConclusionsThis study showed an increase of body weight gain during GnRHa treatment only in girls, which reversed just 1 year after stopping treatment. The overall gain in BMI-SDS with treatment is associated with baseline BMI-SDS.