Delayed Launch of Ultrafast Outflows in the Tidal Disruption Event AT2020afhd by Zikun Lin, Yanan Wang, De-Fu Bu, Junjie Mao, Jifeng Liu

“…Prominent blueshifted absorption features were detected exclusively during the intermediate phase of the event, occurring between days 172 and 212 within the first 300 days postdiscovery. …”
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Murine leukemia virus p12 tethers the capsid-containing pre-integration complex to chromatin by binding directly to host nucleosomes in mitosis. by Madushi Wanaguru, David J Barry, Donald J Benton, Nicola J O'Reilly, Kate N Bishop

“…Nucleosome binding was additionally detected with p12 orthologs from feline and gibbon ape leukemia viruses using both pull-down and BLI assays, indicating that this a common feature of gammaretroviral p12 proteins. …”
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Promoting ‘testicular awareness’: Co‐design of an inclusive campaign using the World Café Methodology by Mohamad M. Saab, Varsha N. Shetty, Megan McCarthy, Martin P. Davoren, Angela Flynn, Ann Kirby, Steve Robertson, Gillian W. Shorter, David Murphy, Michael J. Rovito, Frances Shiely, Josephine Hegarty

“…Data were collected using drawing sheets, artefact cards, sticky notes, coloured markers and a voice recorder. Deductive thematic analysis was conducted. Results Seventeen individuals participated in the study. …”
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Wearable Artificial Intelligence for Sleep Disorders: Scoping Review by Sarah Aziz, Amal A M Ali, Hania Aslam, Alaa A Abd-alrazaq, Rawan AlSaad, Mohannad Alajlani, Reham Ahmad, Laila Khalil, Arfan Ahmed, Javaid Sheikh

“…ObjectiveThis scoping review aims to provide an overview of AI-powered wearable devices used for sleep disorders, focusing on study characteristics, wearable technology features, and AI methodologies for detection and analysis. …”
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Prevalence and factors influencing postpartum depression and its culture-specific cutoffs for women in Asia: a scoping review by Bora Moon, Hyun Kyoung Kim, Ju-Hee Nho, Hyunkyung Choi, ChaeWeon Chung, Sook Jung Kang, Ju Hee Kim, Ju-Young Lee, Sihyun Park, Gisoo Shin, Ju-Eun Song, Min Hee Lee, Sue Kim

“…A literature search was conducted using PubMed, Embase, CINAHL, PsycINFO, and Web of Science. The data analysis focused on demographic characteristics, EPDS cutoffs and features, PPD prevalence, and its associated factors. …”
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Exome sequencing reveals low-frequency and rare variant contributions to multiple sclerosis susceptibility in Turkish families by Furkan Büyükgöl, Berk Gürdamar, Mehmet Ufuk Aluçlu, Yeşim Beckmann, Kaya Bilguvar, Cavit Boz, Alper Bülbül, Sena Destan Bünül, Özge Çetin, Caner Feyzi Demir, Serkan Demir, Taşkın Duman, Hüsnü Efendi, Özgül Ekmekçi, Utku Ertetik, Özlem Ethemoğlu, Elif Everest, Haluk Gümüş, Tuncay Gündüz, Rana Karabudak, Bedriye Karaman, Murat Kürtüncü, Muzaffer Mutluer, Meziyet Dilara Reda, Sabahattin Saip, Meral Seferoğlu, Elif Sever, Osman Ugur Sezerman, Sedat Şen, Beril Taşdelen, Mehmet Tecellioğlu, Murat Terzi, Aslı Tuncer, Ömer Faruk Turan, Melih Tütüncü, Gülgün Uncu, Uğur Uygunoğlu, Cihat Uzunköprü, Umut Voyvoda, Mehmet Fatih Yetkin, Nur Yüceyar, Aksel Siva, Eda Tahir Turanlı

“…Overall, this is one of the first and largest family-based MS studies from Turkey that features a unique cohort from an admixed population that enabled the detection of novel low-frequency and rare variants associated with MS. …”
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Multidisciplinary, Clinical Assessment of Accelerated Deep-Learning MRI Protocols at 1.5 T and 3 T After Intracranial Tumor Surgery and Their Influence on Residual Tumor Perception by Christer Ruff, Till-Karsten Hauser, Constantin Roder, Daniel Feucht, Paula Bombach, Leonie Zerweck, Deborah Staber, Frank Paulsen, Ulrike Ernemann, Georg Gohla

“…<b>Methods</b>: This study uses a multidisciplinary approach involving a neuroradiologist, neurosurgeon, neuro-oncologist, and radiotherapist to evaluate qualitative aspects using a 5-point Likert scale, the preferred reconstruction variant and potential residual tumor of DLR and conventional reconstruction (CR) of FLAIR, T1-weighted non-contrast and contrast-enhanced (T1), and coronal T2-weighted (T2) sequences for 1.5 and 3 T MRI. Quantitative analysis included the image quality metrics Structural Similarity Index (SSIM), Multi-Scale SSIM (MS-SSIM), Feature Similarity Index (FSIM), Noise Quality Metric (NQM), signal-to-noise ratio (SNR), and Peak SNR (PSNR) with CR as a reference. …”
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Follicle-like and other novel structures found in ovaries of aged white rhinoceroses and their potential impact on oocyte recovery rate by R. Appeltant, R. Hermes, S. Holtze, T.B. Hildebrandt, S.A. Williams

“…In addition to known ovarian features, we identified numerous undescribed structural and molecular ovarian characteristics from adult southern white rhinoceros (n=3). …”
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Adaptive respiratory muscle trainer based on hybrid nanogenerator sensor and artificial intelligence by Ziao Xue, Puchuan Tan, Jiangtao Xue, Yuan Xi, Minghao Liu, Yang Zou, Qiang Zheng, Zhou Li, Yuxiang Wu

“…With the help of the principal component analysis algorithm, features related to the fatigue state of muscles were extracted from the collected signals, and the accuracy rate can reach 94.4%. …”
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Microbiological Contamination of Food Raw Materials and Ready-To-Eat Foods: Analytical Review by Andrei S. Khishov, Tatiana V. Balagula, Olga I. Lavrukhina, Aleksey V. Tretyakov, Olga E. Ivanova, Elizaveta S. Kozeicheva

“…The percentage of detections for individual groups of microorganisms was calculated as opposed to their total number. …”
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Assessment of Optical Properties and Monte Carlo-Based Simulation of Light Propagation in Blackhearted Potatoes by Yalin Guo, Yakai He, Xilong Li, Zhiming Guo, Mengyao Zhang, Xiaomei Huang, Zhiyou Zhu, Huabin Jian, Zhilong Du, Huangzhen Lv

“…Based on transmittance (<i>T</i>t), <i>μ</i>_a and <i>μ</i>’_s, Support Vector Machine Discriminant Analysis (SVM-DA) models demonstrated exceptional performance, achieving 95.83–100.00% accuracy in Cross-Validation sets, thereby confirming the robustness and reliability of the optical features for accurate blackheart detection. …”
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A multimodal Neuroimaging-Based risk score for mild cognitive impairment by Elaheh Zendehrouh, Mohammad S.E. Sendi, Anees Abrol, Ishaan Batta, Reihaneh Hassanzadeh, Vince D. Calhoun

“…Structural MRI (sMRI) data provided gray matter (GM) segmentation maps, while resting-state functional MRI (fMRI) data yielded functional network connectivity (FNC) matrices via spatially constrained independent component analysis. Similar imaging features were computed from the UK Biobank (N = 37,780). …”
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Effect of Alkali Source on Crystal Regulation and Ethanol Gas Sensing Properties of Nano-ZnO by Yinying Liao, Lu Qiu, Yunfei Ouyang, Dayang Feng, Shiyi Huang, Zhaoyang Zhang, Xinyao Xie, Junwei Ke, Tianhao Liu, Xiangxiang Chen, Hongshan Bi, Weiran Zuo

“…ZnO were confirmed to be impurity-free through XRD analysis, and their morphological features were characterized by SEM. …”
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Exploring the Effectiveness of Fusing Synchronous/Asynchronous Airborne Hyperspectral and LiDAR Data for Plant Species Classification in Semi-Arid Mining Areas by Yu Tian, Zehao Feng, Lixiao Tu, Chuning Ji, Jiazheng Han, Yibo Zhao, You Zhou

“…How to effectively fuse hyperspectral images (HSI) data with light detection and ranging (LiDAR) to achieve better accuracy in classifying vegetation in semi-arid mining areas is worth exploring. …”
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Clinical and radiographic characteristics of presumptive tuberculosis patients previously treated for tuberculosis in Zambia. by Kondwelani Mateyo, Andrew D Kerkhoff, Ian Dunn, Mutinta S Nteeni, Monde Muyoyeta

“…Patients who reported a prior history of TB treatment were included in the present analysis. 'Confirmed TB' was defined by the detection of TB using Xpert Ultra and/or liquid culture, while 'possible TB' was defined by the receipt of TB treatment without a positive Xpert Ultra or culture result. …”
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Development of a Transfer Learning-Based, Multimodal Neural Network for Identifying Malignant Dermatological Lesions From Smartphone Images by Jiawen Deng, Eddie Guo, Heather Jianbo Zhao, Kaden Venugopal, Myron Moskalyk

“…The multimodal network outperformed the unimodal models on threshold-independent metrics and at MCC-optimised threshold, but it had similar classification performance as the image-only model at high-sensitivity thresholds. Analysis of permutation importance showed that key clinical features influential for the clinical data-based network included bleeding, lesion elevation, patient age and recent lesion growth. …”
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Meta-Ensemble Learning for Heart Disease Prediction: A Stacking-Based Approach With Explainable AI by Mehwish Naz, Aqsa Khalid, Abdul Hameed, Rabia Taj, Waleed Mumtaz, Faiz Abdullah Alotaibi, Mrim M. Alnfiai

“…Overall, the results demonstrate the robustness and practical applicability of the proposed framework for early detection and clinical management of heart disease.…”
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Multi-omics insights into Palmitoylation-mediated brain network remodeling and glioblastoma risk by Shasha Tan, Jinliang You, Huijun Wang, Long Zhao, Shun Li, Xiaoping Tang, Hongjun Liu

“…Our findings suggest that palmitoylation may play a key modulatory role in GBM risk through influencing brain network dynamics, highlighting neuroimaging features (e.g., DMN connectivity, parahippocampal atrophy) as potentially informative for GBM risk and warranting further investigation for their role in early detection. …”
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The influence of systemic inflammatory markers on the development of obstetrical complications in pregnant women with chronic obstructive pulmonary disease by S. M. Heriak, O. I. Oleksiak

“…The aim of our study is to establish the features of changes in the cytokine profile in pregnant women with COPD and their role in the development of obstetrical and perinatal complications. …”
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CHANGES IN URINE MICROFLORA IN CHILDREN WITH COMMUNITY-ACQUIRED URINARY TRACT INFECTION ADMITTED TO HOSPITAL BETWEEN 1990 AND 2015: A RETROSPECTIVE FULL-DESIGN STUDY OF CASE SERIES by Olga A. Zhdanova, Tatyana L. Nastausheva, Irina V. Grebennikova, Galina A. Batishcheva, Irina Yu. Balalaeva

“…It is necessary to study the microbial spectrum of urine in order to determine the features of the urinary tract infection (UTI) course and to make the right choice of a therapeutic approach. …”
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