bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical Value of Fecal Calprotectin in Predicting Mucosal Healing in Patients With Ulcerative Colitis
Authors: Chen Fang , Hu Yue , Fan Yi-Hong , Lv Bin 
Published: August 2021

Aim: This study aimed to evaluate the clinical significance of fecal calprotectin (FC) in assessment of ulcerative colitis (UC) patients' endoscopic patterns and clinical manifestation.Methods: A total of 143 UC patients who received colonoscopy and 108 controls were included. After providing stool samples, patients underwent total colonoscopy. FC was measured by an enzyme-linked immunosorbent assay (ELISA). Clinical activity was based on the Mayo score. Endoscopic findings was scored by the Ulcerative Colitis Endoscopic Index of Severity (UCEIS). Correlation analysis and receiver-operator characteristic (ROC) analysis were carried out to determine the significance of measurements.Results: The median (interquartile range, IQR) of FC levels was 211 (43–990) μg/g in UC and 87.5 (40.50~181) μg/g in the control group. Fecal calprotectin correlated significantly with both Mayo and UCEIS scores (Spearman's r 0.670 and 0.592, P &lt; 0.01). With a cut-off value of 164 μg/g for fecal calprotectin concentration, the area under the curve (AUC) in receiver operator characteristic analysis was 0.830, sensitivity was 85.42%, specificity was 73.68%, positive predictive value (PPV) was 62.12%, and negative predictive value (NPV) was 9.10% in predicting clinical active disease. Similarly, the power of FC to predict mucosal healing (MH) was modest. With a cut-off value of 154.5 μg/g, the AUC was 0.839, sensitivity was 72.34%, and specificity was 85.71%.Conclusion: For evaluating the disease activity of UC, FC is a clinically relevant biomarker for both clinically active disease and MH in patients with UC. But the cut-off value still needs large and multicenter studies for confirmation.
Amble Gait EEG Points at Complementary Cortical Networks Underlying Stereotypic Multi-Limb Co-ordination
Authors: Weersink Joyce B. , Maurits Natasha M. , de Jong Bauke M. 
Published: August 2021

BackgroundWalking is characterized by stable antiphase relations between upper and lower limb movements. Such bilateral rhythmic movement patterns are neuronally generated at levels of the spinal cord and brain stem, that are strongly interconnected with cortical circuitries, including the Supplementary Motor Area (SMA).ObjectiveTo explore cerebral activity associated with multi-limb phase relations in human gait by manipulating mutual attunement of the upper and lower limb antiphase patterns.MethodsCortical activity and gait were assessed by ambulant EEG, accelerometers and videorecordings in 35 healthy participants walking normally and 19 healthy participants walking in amble gait, where upper limbs moved in-phase with the lower limbs. Power changes across the EEG frequency spectrum were assessed by Event Related Spectral Perturbation analysis and gait analysis was performed.ResultsAmble gait was associated with enhanced Event Related Desynchronization (ERD) prior to and during especially the left swing phase and reduced Event Related Synchronization (ERS) at final swing phases. ERD enhancement was most pronounced over the putative right premotor, right primary motor and right parietal cortex, indicating involvement of higher-order organization and somatosensory guidance in the production of this more complex gait pattern, with an apparent right hemisphere dominance. The diminished within-step ERD/ERS pattern in amble gait, also over the SMA, suggests that this gait pattern is more stride driven instead of step driven.ConclusionIncreased four-limb phase complexity recruits distributed networks upstream of the primary motor cortex, primarily lateralized in the right hemisphere. Similar parietal-premotor involvement has been described to compensate impaired SMA function in Parkinson’s disease bimanual antiphase movement, indicating a role as cortical support regions.
Suppression of miR-130a-3p Attenuates Oxygen–Glucose Deprivation/Reoxygenation-Induced Dendritic Spine Loss by Promoting APP
Authors: Zhu Liang , Zhu Lei , Tan Jinyun , Chen Kui , Yu Bo 
Published: August 2021

BackgroundCerebral stroke induces neuronal dysfunction as a consequence of neuronal morphology changes. Emerging evidence suggests that microRNAs (miRNAs) may play an important role in regulating dysfunction in stroke, yet there are still few studies examining the association between whole blood miRNAs and neuronal morphology. The present study aimed to ascertain the potential roles and mechanisms of action of miR-130a-3p in ischemic stroke.MethodsThe miRNA datasets of peripheral serum in the GEO database and the mRNA datasets of the human brain after ischemia were analyzed to identify differentially expressed RNAs, and their functions were verified in cultured neurons in vitro. Furthermore, the target gene was validated by dual-luciferase reporter assay, RT-PCR, Western blot, and immunofluorescence experiments. The identified miRNA was further verified by the OGD test to restore neuronal changes after ischemia through APP.ResultsThe expression of whole blood miR-130a-3p was found significantly lower in participants with ischemic stroke than in controls by analyzing expression profiling datasets of cerebral ischemia stroke obtained from the Gene Expression Omnibus (GEO) DataSets portal, which was confirmed in the MCAO model in mice. Furthermore, GO analysis showed that miR-130a-3p might directly affect neuronal function. Indeed, we demonstrated that miR-130a-3p played a central role in the inhibition of dendritic morphogenesis and in the growth of dendritic spines in vitro. We also confirmed that miR-130a-3p could regulate the expression of APP by luciferase reporter assay, RT-PCR, Western blot, and immunofluorescence experiments, which were consistent with the bioinformatic analysis. Last but not least, we also demonstrated that reducing miR-130a-3p expression partially rescued neuronal morphological changes after OGD in vitro.ConclusionmiR-130a-3p is a potential biomarker of cerebral stroke, can affect neuronal morphology through APP, and promote the repair of neurons by promoting APP expression after cerebral ischemia.
Circulating Tumor DNA to Interrogate the Safety of Letrozole-Associated Controlled Ovarian Stimulation for Fertility Preservation in Breast Cancer Patients
Authors: Rothé Françoise , Lambertini Matteo , Goldrat Oranite , Maetens Marion , Bareche Yacine , Blanc Jeremy , Rouas Ghizlane , Larsimont Denis , Sotiriou Christos , Ignatiadis Michail , Demeestere Isabelle 
Published: August 2021

BackgroundCurrent fertility preservation strategies for young breast cancer patients planning a future motherhood include the association of controlled ovarian stimulation with the aromatase inhibitor letrozole (let-COS) to harvest mature oocytes while maintaining low estradiol levels. Despite this is a widely adopted protocol, the safety of let-COS on breast cancer outcomes has been poorly investigated and its use remains off-label. We assessed the safety of let-COS in breast cancer patients using circulating tumor DNA (ctDNA) as a surrogate biomarker of disease recurrence.MethodsBROVALE is an interventional non-randomized prospective study designed to evaluate the efficacy and safety of let-COS for fertility preservation in early breast cancer patients before starting (neo)adjuvant chemotherapy. Letrozole was administered throughout the COS cycle, until ovulation triggering. Safety was a secondary endpoint. Data on oncological outcomes were collected during the follow-up as well as plasma and whole blood for evaluation of ctDNA levels at the time of enrollment (i.e. before starting let-COS) and oocyte retrieval (i.e. 48 hours after the last administration of letrozole). Targeted gene sequencing on the primary tumor samples was performed to identify specific mutations used for ctDNA analysis by digital PCR. DNA extracted from whole blood samples was used to discriminate between somatic and germline mutations.ResultsFrom April 2014 to May 2017, 29 young early breast cancer patients enrolled in the BROVALE study who had available tissue samples participated to the ctDNA substudy. Among them, 15 had at least one validated somatic mutation. ctDNA was undetectable neither before nor after let-COS in 9 of them. Six patients had detectable ctDNA in the plasma samples collected before Let-COS. No change in ctDNA level after let-COS was observed in 3 patients and the level decreased (fold-change ≤ 0.5) in two women. One patient experienced an increased (fold-change ≥ 2) in ctDNA level but without disease relapse 34 months after diagnosis.ConclusionsNo increase in ctDNA level was observed in 93% (14/15) of the patients receiving let-COS supporting its use as a safe strategy for young women with early breast cancer interested in fertility preservation before chemotherapy.
Amplitude Integrated Electroencephalography and Continuous Electroencephalography Monitoring Is Crucial in High-Risk Infants and Their Findings Correlate With Neurodevelopmental Outcomes
Authors: Lee Inn-Chi , Hong Syuan-Yu , Weng Yi-Ho , Chen Yi-Ting 
Published: August 2021

Background: To evaluate seizure diagnosis in sick infants in the neonatal intensive care unit (NICU) based on electroencephalography (EEG) monitoring combined with amplitude integrated electroencephalography (aEEG).Methods: We retrospectively reviewed EEG and aEEG findings and determined their correlations with neurodevelopmental outcomes at the age of &gt;1 year in 65 patients with diagnosed seizures, encephalopathy, or both.Results: Seizure identification rate was 43.1%. The rate in nonstructural groups (hypocalcemic, hypoglycemic, and genetic seizures) was 71.4%, which was higher (p &lt; 0.05) than the rate of 35.3% of structural brain lesion group [hypoxic–ischemic encephalopathy (HIE) and congenital brain structural malformation]. The aEEG background correlating with neurodevelopmental outcomes had 70.0% positive prediction value (PPV), 65.5%% negative prediction value (NPV), 67.7% specificity, and 67.9% sensitivity (p &lt; 0.005). The aEEG background strongly (PPV, 93.8%; p &lt; 0.005) correlated with the outcomes in HIE. For genetic seizures, the detected rate was high. The ictal recordings for the nonstructural seizures revealed downflected on the aEEG background initially, which differed from the structural lesion.Conclusions: EEG monitoring combined with aEEG can detect seizures, facilitating early treatment. EEG changes during seizures could exhibit delta-theta waves with or without clinical seizures in patients with brain lesions. In non-structural etiologies (hypocalcemic and KCNQ2 seizures), aEEG initially exhibited lower background during seizures that could aid in differentiating these EEG changes from those of other etiologies. The aEEG background was correlated with neurodevelopmental outcome and exhibited high PPV but not NPV in neonatal HIE.
Ginkgo Biloba Extract Is Comparable With Donepezil in Improving Functional Recovery in Alzheimer’s Disease: Results From a Multilevel Characterized Study Based on Clinical Features and Resting-State Functional Magnetic Resonance Imaging
Authors: Zheng Yu , Xie Yi , Qi Ming , Zhang Ling , Wang Wei , Zhang Wanrong , Sha Liju , Wu Jiawen , Li Wanting , Wu Ting 
Published: August 2021

Background: Ginkgo biloba extract (GBE) and donepezil have been reported to be effective in patients with Alzheimer’s disease (AD). Nonetheless, how these drugs impact spontaneous brain activities and how they consequently improve functional recovery are currently unclear.Objectives: This study was to explore the efficacy of GBE vs. donepezil and their add-on efficacy on functional recovery and the adaption of spontaneous brain activities following pharmacologic treatment in patients with AD.Methods: Patients with AD were enrolled and assigned to the GBE group (n = 50), the donepezil group (n = 50), or the combined group (n = 50). Neuropsychological assessments, including minimum mental state examination (MMSE), Alzheimer’s disease assessment scale-cognition (ADAS-Cog), instrumental activity of daily living (IADL), geriatric depression scale (GDS), neuropsychiatric inventory (NPI), and quality of life in Alzheimer’s disease (QOL-AD), were conducted at baseline, 1 month, 3 months, and 6 months. Resting-state functional magnetic resonance imaging (rs-fMRI) was collected to compare the amplitude of low-frequency fluctuation (ALFF), percent amplitude of fluctuation (PerAF), regional homogeneity (ReHo), and degree centrality (DC) at baseline and 6 months.Results: No major significant differences were detected in all comparisons between groups across all follow-up time points. For intragroup comparison, MMSE and ADAS-Cog scores differed significantly across all follow-ups in three groups. The combined group showed significant improvement of GDS scores between baseline and 6 months (p = 0.007). The GBE group (p = 0.044) and donepezil group (p = 0.012) demonstrated significant improvement of NPI scores between baseline and 6 months. Significant correlations were observed between IADL and ALFF in the right gyrus rectus (p = 0.03) and in the left superior cerebellum gyrus (p = 0.01), between GDS and ALFF in the right middle temporal gyrus (p = 0.01), between NPI and PerAF in the left fusiform gyrus (p = 0.03), and between MMSE and ReHo in right superior frontal gyrus (p = 0.04).Conclusion: GBE was comparable with donepezil in the improvement of functional recovery in patients with AD while the combined application of GBE and donepezil seems unnecessary. GBE-mediated improvement of functional recovery was characterized by decreased ALFF values in the right gyrus rectus and decreased PerAF values in the left fusiform gyrus. These featured variations of imaging metrics in specific brain regions may serve as biomarkers in the monitoring of the therapeutic efficacy of GBE.
Applying Machine Learning Approaches to Suicide Prediction Using Healthcare Data: Overview and Future Directions
Authors: Boudreaux Edwin D. , Rundensteiner Elke , Liu Feifan , Wang Bo , Larkin Celine , Agu Emmanuel , Ghosh Samiran , Semeter Joshua , Simon Gregory , Davis-Martin Rachel E. 
Published: August 2021

Objective: Early identification of individuals who are at risk for suicide is crucial in supporting suicide prevention. Machine learning is emerging as a promising approach to support this objective. Machine learning is broadly defined as a set of mathematical models and computational algorithms designed to automatically learn complex patterns between predictors and outcomes from example data, without being explicitly programmed to do so. The model's performance continuously improves over time by learning from newly available data.Method: This concept paper explores how machine learning approaches applied to healthcare data obtained from electronic health records, including billing and claims data, can advance our ability to accurately predict future suicidal behavior.Results: We provide a general overview of machine learning concepts, summarize exemplar studies, describe continued challenges, and propose innovative research directions.Conclusion: Machine learning has potential for improving estimation of suicide risk, yet important challenges and opportunities remain. Further research can focus on incorporating evolving methods for addressing data imbalances, understanding factors that affect generalizability across samples and healthcare systems, expanding the richness of the data, leveraging newer machine learning approaches, and developing automatic learning systems.
Prescribing of long-term antibiotics to adolescents in primary care: a retrospective cohort study
Authors: Lown Mark , McKeown Sam , Stuart Beth , Francis Nick , Santer Miriam , Lewith George , Su Fangzhong , Moore Michael , Little Paul 
Published: August 2021

BackgroundAntibiotic overuse is linked to increased risk of antimicrobial resistance. Long-term antibiotics are commonly used for treating acne and prophylaxis of urinary tract infection. Their contribution to the overall burden of antibiotic use is relatively unknown.AimTo describe the volume of commonly prescribed long-term (≥28 days) antibiotic prescriptions in adolescents and young adults, trends over time, and comparisons with acute prescriptions.Design and settingA retrospective cohort study using UK electronic primary care records.MethodPatients born between 1979 and 1996 and with data in the Care and Health Information Analytics database were included. The main outcome measures were antibiotic prescription rates per 1000 person-years and antibiotic prescription days per person-year between the ages of 11 and 21.ResultsIn total, 320 722 participants received 710 803 antibiotic prescriptions between the ages of 11 and 21 years from 1998 to 2017. Of these 710 803 prescriptions, 191 443 (26.93%) were for long-term antibiotics (≥28 days and ≤6 months in duration). Long-term antibiotics accounted for more than two-thirds (72.48%) of total antibiotic exposure (days per person-year). Total long-term antibiotic prescribing peaked in 2013 at just under 6 days per person-year and declined to around 4 days in 2017.ConclusionAmong adolescents and young adults, exposure to long-term antibiotics (primarily lymecycline used for acne) was much greater than for acute antibiotics and is likely to make an important contribution to antimicrobial resistance. Urgent action is needed to reduce unnecessary exposure to long-term antibiotics in this group. Increasing the use of, and adherence to, effective non-antibiotic treatments for acne is key to achieving this.
The Effect of Incentivized Electronic Word-of-Mouth (EWOM) on Consumer Purchase Intention
Authors: Tamrin Muhammad Husni , Huda Nurul 
Published: August 2021

Objective: Social media has a strong impact as a reference for consumers in getting information about the product. Electronic word-of-mouth (eWOM), which is usually delivered by social media, is still the most secure advertising media. This study provides information about incentivized eWOM on purchase intention and other factors that can affect consumers. Research Design & Methods: The method used in this research is the quantitative method with an associative approach. Descriptive analysis and structural equation modeling were used to measure the influence of these variables. Findings: The results showed that the incentivized eWOM had a significant effect on purchase intention but had no impact on the company’s brand awareness. Meanwhile, the attractiveness of advertising messages has no significant effect in influencing purchase intention but has a significant effect on the company’s brand awareness. Implications & Recommendations: Although this research give contributions to the e-WOM literature, several limitations and future research suggestion deserve mentions. Further research can examine the relative effectiveness of non-monetary incentives. Contribution & Value Added: Researchers have provided input and suggestions to SMEs to optimize incentivized eWOM to increase consumer purchase intention.
The Creation of Intention To Buy through Online Social Ties and Social Media Advertisement
Authors: Roosdhani M. Rifqy , Komaryatin Nurul 
Published: August 2021

Objective: The growing number of social media users makes many companies want to get subscribers through their social media activities. There are several choices of strategies that can be done by the company to be able to take the huge market. Research Design & Methods: This study compares the effect of advertising activity on social media and user group development that has a strong tie to intention to buy. Findings: This research found that the social media advertisements has a better impact to intention to buy compared to social ties. Implications & Recommendations: This study was conducted on social media users on land Transportation Company that already has a group in social media, Facebook, and does advertising activities on it. Contribution & Value Added: The results of this study provide theoretical implications in the verification of the previous research results and managerial implications that can help the company in conducting marketing activities through social media.
PENERAPAN MODEL PEMBELAJARAN ADDIE TERHADAP HASIL BELAJAR SISWA PADA MATA PELAJARAN FIQIH
Authors: Qori Amarullah Risal , Fatmah Wahidah Nida 
Published: August 2021

Penelitian ini bertujuan untuk mengetahui pengaruh penerapan model pembelajaran ADDIE pada mata pelajaran Fikih terhadap hasil belajar siswa kelas VIII Siswa SMPIT Plus Al Ittihad Cianjur tahun ajaran 2020/2021. Metode yang digunakan pada penelitian ini adalah Quasi Eksperimen. Pada populasi penelitian ini yaitu seluruh siswa kelas VIII yang terdiri dari 8 kelas. sampel pada penelitian ini yaitu kelas VIII A yang berjumlah 30 siswa. Instrumen penelitian berupa soal uraian. Teknik pengumpulan data yang digunakan yaitu tes dan observasi. Teknik analisis data menggunakan SPSS 26.0. Berdasarkan analisis dari hasil hipotesis di atas dapat disimpulkan bahwa nilai sig adalah 0,000. Karena nilai sig < 0,05, maka Ho ditolak, H1 diterima sehingga disimpulkan bahwa terdapat perbedaan hasil belajar fiqih dengan model pembelajaran konvensional dan dengan menggunakan model pembelajaran ADDIE, dengan kata lain pengunaan model pembelajaran ADDIE sangat efektif dalam meningkatkan hasil belajar fiqih siswa. Pelaksanaan penerapan model pembelajaran ADDIE pada mata pelajaran Fiqih dengan tema “Kurban” SMPIT Plus Al Ittihad Cianjur dengan menerapkan langkah-langkah pembelajaran ADDIE yaitu, analisis, desain, pengembangan, implementasi dan evaluasi
Identifikasi Keterlaksanaan Pembelajaran PJOK Tingkat SMP Di Masa Pandemi Covid 19 Se-Kabupaten Sidoarjo
Authors: Rochman Baitur , Indahwati Nanik , Priambodo Anung 
Published: August 2021

Tujuan dari penelitian ini adalah untuk mengetahui keterlaksanaan pembelajaran PJOK tingkat SMP di masa pandemic COVID-19 Se-Kabupaten Sidoarjo. Penelitian ini merupakan penelitian deskriptif kuantitatif dengan menggunakan satu variable tanpa membuat perbandingan dengan variabel lainnya. Metode yang digunakan adalah survey dengan menggunakan teknik penyebaran angket dan Dokumentasi. Populasi penelitian adalah seluruh guru olahraga dalam anggota MGMP PJOK sejumlah 130 guru se-Kabupaten Sidoarjo. Sampel penelitian sebanyak 100 dari sejumlah total 130 guru olahraga se- Kabupaten Sidoarjo yang dipilih secara acak sesuai prosentase jumlah keseluruhan guru. Alat ukur yang digunakan pada variabel keterlaksanaan pembelajaran PJOK adalah kuesioner dengan skala Likert yang memiliki bobot skor 1-5. Sampel penelitian mengisi angket yang diberikan dengan me-checklist pada kolom dan pemberian bobot sesuai dengan lima alternatif jawaban yang telah disediakan, mulai dari sangat setuju, setuju, ragu-ragu, tidak setuju, dan sangat tidak setuju. Skala untuk pernyataan bersifat favourable dan unfavourable. Hasil penelitian menunjukkan bahwa tingkat keterlaksanaan pembelajaran PJOK tingkat SMP di Masa Pandemi COVID-19 seluruh guru olahraga SMP se-Kabupaten Sidoarjo berada pada kategori “sangat rendah” sebesar 8% (8 guru), “rendah” sebesar 15.0% (15 guru), “sedang” sebesar 46% (46 guru), “tinggi” sebesar 26.0% (26 guru), dan “sangat tinggi” sebesar 5% (5 peserta didik). Berdasarkan nilai rata-rata, yaitu 89.62, identifikasi tingkat keterlaksanaan pembelajaran PJOK tingkat SMP di Masa Pandemi COVID-19 seluruh guru olahraga SMP se-Kabupaten Sidoarjo berada pada tingkatan “sedang”.