Clinical Course of Untreated and Treated Chronic Hepatitis B in Pregnant Patients: A Prospective Study by Yasemin Nadir, Ayse Batirel, Ayse Yasemin Karsidag, Fatma Kaya Narter, Ahmet Nadir

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Proteomic analysis reveals the difference between the spermatozoa of young and old Sus scrofa by Shuhao Fan, Fan Xie, Qianqian Wang, Haibo Ye, Yali Tian, Yangguang Liu, Huibin Zhang, Xianrui Zheng, Zongjun Yin, Xiaodong Zhang

“…In this investigation, spermatozoa from three one-year-old and three seven-year-old Wannan black pigs were individually chosen. …”
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An Ultra‐Short‐Term Multi‐Step Prediction Model for Wind Power Based on Sparrow Search Algorithm, Variational Mode Decomposition, Gated Recurrent Unit, and Support Vector Regressio... by Yulong Chen, Xue Hu, Xiaoming Liu, Lixin Zhang

“…The proposed model was evaluated against seven others using three error metrics: MAE, RMSE, and R2, along with their corresponding enhancement percentages. …”
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Sildenafil as a Salvage Treatment for Ovarian Torsion: A Rat Model by Didem Alkas Yaginc, Huriye Ayse Parlakgümüs, Selcuk Yetkinel, Pinar Caglar Aytac, Huriye Eda Ozturan Ozer, Derya Akaydin Aldemir, Esra Bulgan Kilicdag

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The Influence of Perceptions of Risks and Benefits on the Continuity of Use of Fintech Services by Artur Barretti Mascarenhas, Cristiane Koda Perpétuo, Erika Borgonovo Barrote, Maria Paula Perides

“…The data collection was performed through an electronic survey, distributed through social networks during May and June of 2019. The main results confirmed seven of the eleven initial hypotheses, highlighting that the perceived benefits, especially the economic ones, were relevant to early adopters and seamless transactions were relevant for late adopters. …”
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Comparative Analysis of Tillage Indices and Machine Learning Algorithms for Maize Residue Cover Prediction by Jian Li, Kewen Shao, Jia Du, Kaishan Song, Weilin Yu, Zhengwei Liang, Weijian Zhang, Jie Qin, Kaizeng Zhuo, Cangming Zhang, Yu Han, Yiwei Zhang, Bingrun Sui

“…Remote sensing estimation of maize residue cover (MRC) can rapidly acquire large-scale data on MRC, crucial for monitoring and promoting conservation tillage. Herein, seven tillage indices derived from Sentinel-2 satellite imagery were analyzed alongside measured MRC data to assess their correlation with MRC. …”
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Defining indicators for disease burden, health outcomes, policies and barriers and facilitators to health services for migrant populations in the Middle East and North African regi... by Charles Agyemang, Ali Ardalan, Farah Seedat, Bouchra Assarag, Nuria Casamitjana, Kolitha Wickramage, Sally Hargreaves, Ana Requena-Mendez, Fouad M Fouad, Dominik Zenner, Anna Deal, Stella Evangelidou, Wafa Saidi, Chiaki Ito, Oumnia Bouaddi, Moudrick Abdellatifi, Alba Cuxart-Graell, Hassan Edries, Eman Elafef, Taha Maatoug, Anissa Ouahchi, Liv Mathilde Pampiri, Sara Arias, Adel Abdelkhalek, Ahmed Hamed Arisha, Ibrahim Ahmed Bani, Aasmaa Chaoui, Wafa Chemao-Elfihri, Kenza Hassouni, Mahmoud Hilali, Mohamed Khalis, Wejdene Mansour, Ali Mtiraoui, MENA Migrant Health Working Group, Asad Adam, Adnene Ben Haj Aissa, Salma Altyib, Hanen Ben Belgacem, Imane Belkhammar, Thomas Calvot, Luciana Ceretti, Nelly Chavassieux, Hassan Chrifi, Mohamed Douagi, Algdail Elnil, Gonzalo Fanjul, Ahmed Hamed, Abdedayem Khelifi, Lora Makhlouf, Maissa Mokni, Davide Olchini, Tarik Oufkir, Nasong Park, Giuseppe Raffa, Sandra Santafé, Alice Sironi, Fatma Temimi, Zeineb Turki

“…This protocol describes a suite of seven systematic reviews that aim to identify, appraise and synthesise the available evidence on the burden and health outcomes, policies and access (barriers and facilitators) related to these mobile populations in the region.Methods Seven systematic reviews will cover three questions to explore the: (1) burden and health outcomes, (2) policies and (3) healthcare barriers and facilitators for the following seven disease areas in migrants in the MENA region: tuberculosis, HIV and hepatitis B and C, malaria and neglected tropical diseases, diabetes, mental health, maternal and neonatal health, and vaccine-preventable diseases. …”
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Machine Learning Does Not Improve Humeral Torsion Prediction Compared to Regression in Baseball Pitchers by Garrett S Bullock, Charles A Thigpen, Gary S Collins, Nigel K Arden, Thomas K Noonan, Michael J Kissenberth, Ellen Shanley

“… # Results Four hundred and seven pitchers (Age: 23.2 +/-2.4 years, body mass index: 25.1 +/-2.3 km/m^2^, Left-Handed: 17%) participated. …”
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Analysis of Aerosol Type and Fine- and Coarse-mode Aerosol Direct Radiative Forcing over Regions in East and Southeast Asia Based on AERONET Version 3 Data by Jianyu Lin, Xinyong Shen, Lizhu Xing, Huizheng Che, B. N. Holben

“…Abstract Based on the particle linear depolarization ratio (PLDR) and single-scattering albedo (SSA) values obtained for 1020 nm from Aerosol Robotic Network (AERONET) Version 3 Level 2.0 data collected in five regions, namely, northern China, Northwest Asia, the Tibetan Plateau, southern China and Southeast Asia, we classified seven types of aerosol (viz., purely dust, dust-dominated, pollution-dominated, non-absorbing [NA], weakly absorbing [WA], moderately absorbing [MA] and strongly absorbing [SA]) in order to assess the spatial and temporal distributions of their constituents and the radiative effects of their fine- and coarse-mode particles. …”
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The role of SASP in ischemic stroke: a deep dive into cellular mechanisms by Dong Xie, Yang Liu, Fang-Biao Xu, Jin-Sheng Zhang

“…Finally, authenticated core gene expression in serum of MCAO and Sham rats using real-time fluorescent polymerase chain reaction (RT-qPCR).ResultsFourteen hub genes were discerned. Seven cell types were annotated in MCAO mouse peripheral blood single-cell data. …”
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Automated Detection of Macular Diseases by Optical Coherence Tomography and Artificial Intelligence Machine Learning of Optical Coherence Tomography Images by Soichiro Kuwayama, Yuji Ayatsuka, Daisuke Yanagisono, Takaki Uta, Hideaki Usui, Aki Kato, Noriaki Takase, Yuichiro Ogura, Tsutomu Yasukawa

“…The remaining 100 images were used to evaluate the trained convolutional neural network (CNN) model. Results. Automated disease detection showed that the first candidate disease corresponded to the doctor’s decision in 83 (83%) images and the second candidate disease in seven (7%) images. …”
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Baicalein inhibits PRRSV through direct binding, targeting EGFR, and enhancing immune response by Jing Wu, Qi Lu, Jing Hou, Yueqin Qiu, Min Tian, Li Wang, Kaiguo Gao, Xuefen Yang, Zongyong Jiang

“…However, there is little information about the effects and mechanisms of baicalein in relation to PRRSV. In this study, a network pharmacology analysis identified seven potential targets of baicalein against PRRSV, with the epidermal growth factor receptor (EGFR) emerging as the core target. …”
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Meaningful Engagement as a Cornerstone for Implementing the Key Recommendations to Advance the Sexual and Reproductive Health and Rights of Women Living With HIV Across Policy, Pra... by Zoë Osborne MPH, Muluba Habanyama, Brittany Cameron, Alexandra de Pokomandy MD, MSc, Brenda Gagnier, Elizabeth King MD, Jill Koebel MPH, Mona Loutfy MD, MPH, Carrie Martin BA, BSW, Renée Masching MSW, Manjulaa Narasimhan PhD, Valerie Nicholson, Neora Pick MD, Stephanie Smith, Shelly Tognazzini BA, Wangari Tharao PhD, Angela Kaida PhD

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Evaluation of Associated Structural and Chromosomal Abnormalities in Patients with Fetal Cerebral Ventriculomegaly Detected in Ultrasonographic Imaging by Erkan Cagliyan, Samican Ozmen, Sureyya Saridas Demir, Ceren Aydin, Egehan Bilen, Handan Guleryuz, Elif Yasar, Derya Ercal, Elcin Bora, Tufan Cankaya

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A Huge Innovation in Diagnosis of Obstructive Sleep Apnea Syndrome: With an Artificial Intelligence-Based Algorithm, Obstructive Sleep Apnea Syndrome Can Now Be Diagnosed With Pulm... by Seval Bulut Eris, Mehmet Recep Bozkurt, Omer Eris, Cahit Bilgin

“…The models obtained by hyperparameter optimization and cross-validation were tested with unseen data, and their performance was evaluated using seven different criteria. Using only five features extracted from the flow-volume curve (TLC/PIF, PIF/PEF, TLC/FIF50, TLC/FIF25, and FIF25/FEF25), OSAS was diagnosed with 97.1% accuracy using the Neural Network (NN) algorithm. …”
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Effects of Revised Toll-by-Weight Policy on Truck Overloading Behavior and Bridge Infrastructure Damage Using Weigh-in-Motion Data: A Comparative Study in China by Haiyun Huang, Junyong Zhou, Junping Zhang, Wangxi Xu, Zhixing Chen, Ningning Li

“…This study’s findings can support future efforts by the Chinese government to further refine their toll-by-weight policies and subsequently ensure a safe and viable transportation network.…”
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Readability and understandability of clinical research patient information leaflets and consent forms in Ireland and the UK: a retrospective quantitative analysis by Peter Doran, Eilish McAuliffe, Lydia O'Sullivan, Prasanth Sukumar, Rachel Crowley

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Inflammation biomarkers and neurobehavioral performance in rural adolescentsKey PointsRelevance by Beemnet Amdemicael, Kun Yang, Briana N.C. Chronister, Caroline Mackey, Xin Tu, Sheila Gahagan, Danilo Martinez, Harvey Checkoway, David R. Jacobs, Jr., Jose Suarez-Torres, Suzi Hong, Jose R. Suarez-Lopez

“…Cytokines can alter neural network activity to induce neurocognitive changes. …”
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Factors Influencing Treatment-Seeking Behavior Among Caregivers of Children with Cancer: A Scoping Review by Nurhidayah I, Hendriyani D, Adistie F, Nurhaeni N, Mediani HS

“…Expanding the cancer service network in developing countries could improve public access to pediatric cancer services.Keywords: children, factors, cancer, treatment delayed, health-seeking behavior…”
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Health and economic impact of oral PrEP provision across subgroups in western Kenya: a modelling analysis by Linxuan Wu, Sarah Cox, Monisha Sharma, Brian Pfau, Rachel Wittenauer

“…We assessed the health and economic impact of PrEP scale-up among different subgroups and regions in western Kenya.Methods We adapted an agent-based network model, EMOD-HIV, to simulate PrEP uptake in six counties of western Kenya across seven subgroups including serodiscordant couples (SDCs), adolescent girls and young women (AGYW), adolescent boys and young men, women with multiple partners and men with multiple partners. …”
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