Modeling the Impacts of Galaxy Intrinsic Alignments on Weak Lensing Peak Statistics by Tianyu Zhang, Xiangkun Liu, Ziwei Li, Chengliang Wei, Guoliang Li, Yu Luo, Xi Kang, Zuhui Fan

“…Weak gravitational lensing (WL) peak statistics capture cosmic nonlinear structures and can provide additional cosmological information complementary to cosmic shear two-point correlation analyses. …”
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Diabetes and periodontitis: the role of a high-glucose microenvironment in periodontal tissue cells and corresponding therapeutic strategies by Dan-dan Xiang, Yu-xin Sun, Chen Jiao, Yu-qian Guo, Yu-xiang Fei, Bai-qiang Ren, Xiao-Tao He, Xuan Li

“…Both of these diseases affect many people worldwide. Epidemiological data have revealed a close relationship between periodontitis and diabetes. …”
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A vegetation strategy to balance the hazardous level of microplastics in the land–sea interface through rhizosphere remediation by Weifeng Ruan, Yanqin Peng, Xi Ling, Bailun Yu, Yiping Tai, Nora Fung-Yee Tam, Yunv Dai, Yang Yang

“…The growth environments and physiological structures of aquatic plants and terrestrial plants differed, resulted in a greater potential for the root systems of aquatic plants to capture MPs. …”
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Evaluation of the oil and gas preservation conditions, source rocks, and hydrocarbon-generating potential of the Qiangtang Basin: New evidence from the scientific drilling project by Li-jun Shen, Jian-yong Zhang, Shao-yun Xiong, Jian Wang, Xiu-gen Fu, Bo Zheng, Zhong-wei Wang

“…Moreover, the Qiangtang Basin has favorable oil and gas preservation conditions, as verified by the comprehensive study of the sealing capacity of seals, basin structure, tectonic uplift, magmatic activity, and groundwater motion. …”
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Sphingosine 1-Phosphate Receptor 1 Is Required for MMP-2 Function in Bone Marrow Mesenchymal Stromal Cells: Implications for Cytoskeleton Assembly and Proliferation by Chiara Sassoli, Federica Pierucci, Alessia Tani, Alessia Frati, Flaminia Chellini, Francesca Matteini, Ambra Vestri, Giulia Anderloni, Daniele Nosi, Sandra Zecchi-Orlandini, Elisabetta Meacci

“…Notably, active S1PR1/MMP-2 signalling is required for F-actin structure assembly (lamellipodia, microspikes, and stress fibers) and, in turn, cell proliferation. …”
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Epidemiological and clinical features of lymphoproliferative diseases in the head and neck region by F. Sh. Kamolova, A. M. Mudunov, P. A. Zeynalova, L. Yu. Grivtsova, G. F. Allakhverdieva, R. I. Azizyan, A. A. Akhundov, I. A. Zaderenko, M. V. Bolotin, D. K. Stelmakh, V. I. Sokorutov, K. D. Il’kaev, V. T. Tsiklauri, I. M. Gelfand, M. B. Pak, O. L. Timofeeva, Yu. E. Ryabukhina, F. M. Abbasbeyli, Ts. Chzhao

“…The high heterogeneity of lymphomas in the head and neck area requires structuring knowledge about their epidemiology and clinical manifestations.Objective: to study the epidemiological and clinical features of the head and neck lymphoproliferative diseases, which will lead to an improvement in diagnostic quality of this nosology’s.Materials and methods. …”
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Prevalence, awareness, treatment and control of arterial hypertension depending on regional characteristics in Russia: results of the ESSE-RF study 2012-2022 — evidence of COVID-19... by S. A. Maksimov, S. A. Shalnova, Yu. A. Balanova, A. E. Imaeva, V. A. Kutsenko, M. B. Kotova, G. A. Muromtseva, S. E. Evstifeeva, A. V. Kapustina, N. S. Karamnova, O. B. Shvabskaya, T. V. Repkina, T. O. Gonoshilova, A. V. Kudryavtsev, N. I. Belova, L. L. Shagrov, M. A. Samotrueva, A. L. Yasenyavskaya, O. A. Bashkina, S. V. Glukhovskaya, I. A. Levina, E. A. Shirshova, E. B. Dorzhieva, E. Z. Urbanova, N. Yu. Borovkova, V. K. Kurashin, A. S. Tokareva, Yu. I. Ragino, G. I. Simonova, A. D. Khudyakova, V. N. Nikulin, O. R. Aslyamov, G. V. Khokhlova, A. V. Solovieva, A. A. Rodionov, O. V. Kryachkova, Yu. Yu. Shamurova, E. V. Mikhailov, Yu. O. Tarabrina, M. G. Ataev, M. O. Radzhabov, Z. M. Gasanova, M. A. Umetov, I. A. Hakuasheva, L. V. Elgarova, E. I. Yamashkina, L. A. Balykova, A. A. Usanova, A. M. Nikitina, N. V. Savvina, Yu. E. Spiridonova, E. A. Naumova, V. S. Yudin, A. A. Keskinov, S. M. Yudin, A. V. Kontsevaya, O. M. Drapkina

“…A demographic shift toward a younger age structure in regions was associated with a decreased AH probability (0.83; 0.76-0.91). …”
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Exploration of the clinical prognostic model of BRCA based on PCAT7 by Zhi Zhang, Chaocheng Xiang, Tong Chen, Aimin Ma, Xu Wang, Jiaying Li, Yixuan Chen, Yixuan Chen, Chengyu Huang, Chengyu Huang, Ting Li, Ting Li, Danmei Wu, Steven Mo, Dequan Li

“…Consequently, investigating the function and prognostic significance of PCAT7 in BRCA has become imperative.MethodsThis study used BRCA data from the Cancer Genome Atlas (TCGA) as a training cohort to evaluate the prognostic potential of PCAT7. …”
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Features of lymph node metastasis depending on intratumoral heterogeneity of non-small cell lung cancer in patients with different morphological changes in the bronchial epithelium by M. V. Zavyalova, D. M. Loos, D. S. Pismenny, A. A. Durova, E. S. Andryukhova, E. O. Rodionov, S. V. Miller, S. A. Tuzikov, O. V. Pankova, L. A. Tashireva, S. V. Vtorushin, V. M. Perelmuter

“…In the parenchymal component of squamous cell carcinoma, 5 types of structures were distinguished: with keratinization, consisting of atypical cells of the prickly type without keratinization, consisting of atypical cells of the basaloid type, built of atypical cells with pronounced polymorphism, single tumor cells. …”
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MSAN-Net: An End-to-End Multi-Scale Attention Network for Universal Industrial Defect Detection by Zelu Wang, Ming Luo, Xinghe Xie, Yue Sun, Xinyu Tian, Zhengxuan Chen, Junwei Xie, Qinquan Gao, Tong Tong, Yue Liu, Tao Tan

“…MSAN-Net was adopted an integrated architecture, deeply combining UnifiedViT, C2f modules, convolution operations, SPPF structure, and Bi-Level Routing Attention mechanism to achieve accurate identification of complex industrial defects. …”
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Normalization of tumor vasculature by imiquimod: proposal for a new anticancer therapeutic indication for a TLR7 agonist by Jarosz-Biej Magdalena, Czapla Justyna, Ciepła Joanna, Smolarczyk Ryszard, Drzyzga Alina, Sprus-Lipka Dorota, Pilny Ewelina, Matuszczak Sybilla, Cichoń Tomasz

“…Despite studies conducted, there are no unambiguous data showing how IMQ affects the condition of tumor blood vessels. …”
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Inhibition Mechanism of Pleurotus citrinipileatus Sing. Ergothioneine on Pancreatic Lipase Activity by Zhangchen XIA, Xiaohui MENG, Ru FANG, Yanqing MAO, Junwen CHENG, Yanbin WANG, Juan XU, Liang HE

“…The UV spectrum indicated there was a π→π* transition produced by the peptide bond C=O group of PL as the mass concentration of PCEGT increased, which could reflect the reinforcement of polarity and hydrophilicity. Fluorescence spectra data revealed PCEGT could efficiently static-quench the intrinsic fluorescence of PL by changing its space structure. …”
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Comparative Genomics and Characterisation of the Role of <i>Saccharomyces cerevisiae</i> Respiration in the Fermentation of Chinese Steamed Bread by Yawen Gao, Yufeng Guo, Jianing Pang, Mingkai Liu, Tengdan Yuan, Qinhong Wang, Jingsheng Liu

“…At the micro level, CSBs 1, 25 and 33 showed a loose reticular structure with large holes and in which starch particles wrapped into gluten protein. …”
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Turbulent Transport Efficiency of Momentum and Sscalar over Forest Canopy in Southern Sichuan by Yi DING, Yu ZHANG, Demin FAN, Youqi SU, Qian ZHANG, Yanqi WANG, Yanqi WANG

“…The turbulent transport characteristics of momentum and scalar over the canopy were studied by using the three levels （20 m， 38 m and 56 m） turbulence data measured at the 60m forest micro meteorological tower in southern Sichuan from May 1 to June 30， 2021.Coherent structure is the main form of turbulent motion， which is composed of updraft （ejection） and downdraft （sweep）.In this paper， the quadrant analysis method is used to analyze the boundary of the roughness sublayer， roughness sublayer and constant flux layer above the forest canopy and the ejection-sweep motion characteristics of the constant flux layer， including the difference of ejection and sweep contribution to flux， the difference between momentum and scalar transport， and the difference between different scalar （T， q， CO2） transport.The results show that under unstable and stable conditions， the ejection dominates the scalar transport at all three levels， while the sweep is the main eddy current motion for scalar transport above the roughness sublayer under neutral conditions.For the momentum flux， under unstable conditions， the ejection dominates at all three levels.Under stable conditions， the ejection dominates at the roughness sublayer and the constant flux layer， while at the boundary of the roughness sublayer and the constant flux layer， the effect of the sweep is greater than that of the ejection.Under neutral conditions， the flux contribution of the sweep is greater than that of the ejection except for the roughness sublayer.The third-order cumulant expansion method （CEM） can more accurately express the flux contribution caused by ejection and sweep， while the incomplete cumulant expansion method （ICEM） is poor in simulating the temperature at the boundary of roughness sublayer and constant flux layer.Through the calculation of transmission efficiency， the difference between momentum and scalar transmission is further quantified.The turbulent transfer efficiency of momentum decreases with increasing instability， while the heat transfer efficiency is the opposite.Atmospheric stability is an important factor controlling momentum and scalar transfer， and the transfer efficiency of water vapor is less affected by atmospheric stability.Under the condition of strong instability， the heat transfer efficiency is more effective than other scalar transfer.…”
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A Hybrid Deep Learning Framework for Deepfake Detection Using Temporal and Spatial Features by Fazeel Zafar, Talha Ahmed Khan, Salas Akbar, Muhammad Talha Ubaid, Sameena Javaid, Kushsairy Abdul Kadir

“…Our research introduces a model for detecting deepfakes by utilizing an Enhanced EfficientNet B0 structure in conjunction with Temporal Convolutional Neural Networks (TempCNNs). …”
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Radiologic assessment of the optimal point for tube thoracostomy using the sternum as a landmark: a computed tomography‐based analysis by Jaeik Jang, Jae-Hyug Woo, Mina Lee, Woo Sung Choi, Yong Su Lim, Jin Seong Cho, Jae Ho Jang, Jea Yeon Choi, Sung Youl Hyun

“…Purpose This study aimed at developing a novel tube thoracostomy technique using the sternum, a fixed anatomical structure, as an indicator to reduce the possibility of incorrect chest tube positioning and complications in patients with chest trauma. …”
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Spatio-temporal dynamics of Isoberlinia-dominated woodlands in disturbance-prone landscapes over 15 years by Shègoun Eudes Idjigbèrou, Eméline Sêssi Pélagie Assédé, Séverin Biaou, Gérard Nounagnon Gouwakinnou, Armand Kuyema Natta, Samadori Sorotori Honoré Biaou

“…Productivity and disturbance influence species richness and structure, enhancing our understanding of vegetation dynamics and species coexistence over time. …”
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Qualitative and Quantitative Blood Cell Disorders Among High‐Level Antiretroviral Therapy‐Experienced Children in Northwest Ethiopia: A Cross‐Sectional Study by Dereje Mengesha Berta, Biruk Bayleyegn, Solomon Getawa, Zewudu Mulatie, Tiruneh Adane, Elias Chane, Bisrat Birke Teketelew, Melak Aynalem

“…The data were entered into EPI‐Info version 3.5.3 and then transferred to SPSS version 25 for analysis. …”
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Atrophy of hypothalamic subregions increases migraine risk: cross-sectional study and mendelian randomization analysis by Zhonghua Xiong, Lei Zhao, Geyu Liu, Dong Qiu, Yanliang Mei, Xiaoshuang Li, Zhi Guo, Peng Zhang, Mantian Zhang, Tianshuang Gao, Jinju Sun, Xin Liu, Yonggang Wang

“…Abstract Background The hypothalamus is a versatile structure comprising several nuclei that play key roles in regulating various biological processes associated with migraine, including hormone secretion, metabolism, circadian rhythm, and autonomic nervous system functions. …”
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A deep machine learning model development for the biomarkers of the anatomical and functional anti-VEGF therapy outcome detection on retinal OCT images by B.E. Malyugin, S.N. Sakhnov, L.E. Axenova, K.D. Axenov, E.V. Kozina, V.V. Vronskaya, V.V. Myasnikova

“…To automatize the processes of identifying morphological structures in OCT images deep learning methods are used. …”
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