The role of gut microbiota in modulating brain structure and psychiatric disorders: A Mendelian randomization study by Zheng Ye, Yingying Gao, Jiaqi Yuan, Feng Chen, Peng Xu, Wenbin Liu

“…In this study, we employed a mediation Mendelian randomization approach to delve into the potential causal relationships between gut microbiota and psychiatric disorders, with a focus on the mediating role of brain structural changes. We harnessed genetic data from large - scale genome - wide association studies to analyze how 196 gut microbiota taxa affect ten psychiatric disorders via alterations in 3143 brain structures.Our key findings revealed significant bidirectional causal relationships. …”
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Numerical Study of Surrounding Rock Damage in Deep-Buried Tunnels for Building-Integrated Underground Structures by Penglin Zhang, Chong Zhang, Weitao Chen, Chunhui He, Yang Liu, Zhaofei Chu

“…Understanding the distribution characteristics of rock damage zones under these conditions is crucial for the design and safety of building-integrated underground structures. This study investigates the relationship between surrounding rock damage and in situ stress conditions through numerical simulation methods. …”
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COMPARATIVE STUDY OF THE EFFECT OF REGENERATION STIMULATION DRUG ON THE STRUCTURE AND RATE OF HAIR GROWTH IN WHITE RATS by Olga B. Zhdanova, Iraida I. Okulova, Elena B. Dunaeva, Olga V. Chasovskikh

“…The study of the activation process of hair papilla stem cells when using regeneration stimulators to improve the structure of the hair and its growth rate is relevant both for the development of drugs for fur farming and alopecia treatment regimens. …”
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Auto-resolving the atomic structure at van der Waals interfaces using a generative model by Wenqiang Huang, Yucheng Jin, Zhemin Li, Lin Yao, Yun Chen, Zheng Luo, Shen Zhou, Jinguo Lin, Feng Liu, Zhifeng Gao, Jun Cheng, Linfeng Zhang, Fangping Ouyang, Jin Zhang, Shanshan Wang

“…Abstract The high-resolution visualization of atomic structures is significant for understanding the relationship between the microscopic configurations and macroscopic properties of materials. …”
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SIGNS OF POST-TRAUMATIC STRESS DISORDER IN COMBATANTS WITH DIFFERENT COMBAT EXPERIENCE AND THE STRUCTURE OF THEIR PSYCHOLOGICAL REHABILITATION by Ivan М. Okhrimenko, Nataliia O. Bilevych, Maryna Yu. Halych, Yaroslav V. Halych, Natalia E. Penkova, Petro V. Kozyra, Oksana G. Strelchenko

“…To study the signs of post-traumatic stress disorder in combatants depending on the duration of their participation in combat operations and to substantiate the structure of their psychological rehabilitation. …”
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Evolution law of microporous structure in cement asphalt (CA) mortar under the action of polyurethane polycarboxylates by Shuncheng Xiang, Ming Yuan, Xin Yang, Lulu Li, Yingli Gao, Haotian Yu, Huan Zhou, Tingxiang Zheng, Jin Zhang, Zhen Jiang

“…According to the analysis of fractal dimension and nuclear magnetic resonance test data, the Cement Asphalt (CA) mortar ‘s pore volume fractal dimension is greater than 3, indicating that the pore structure has fractal characteristics. …”
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Features of formation of grain sorghum yield structure elements in dependence on inter-row spacing and fertilizing by В. М. Найденко

“…Laboratory, field, statistical. Results. Data on features of structural elements formation and productivity of grain sorghum in dependence on varietal characteristics, inter-row spacing and level of mineral nutrition are presen­ted. …”
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Automatic Segmentation of the Infraorbital Canal in CBCT Images: Anatomical Structure Recognition Using Artificial Intelligence by Ismail Gumussoy, Emre Haylaz, Suayip Burak Duman, Fahrettin Kalabalık, Muhammet Can Eren, Seyda Say, Ozer Celik, Ibrahim Sevki Bayrakdar

“…<b>Background/Objectives:</b> The infraorbital canal (IOC) is a critical anatomical structure that passes through the anterior surface of the maxilla and opens at the infraorbital foramen, containing the infraorbital nerve, artery, and vein. …”
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Analyzing canopy structure effects based on LiDAR for GPP-SIF relationship and GPP estimation by Shuo Shi, Shuo Shi, Shuo Shi, Shuo Shi, Zixi Shi, Fangfang Qu, Wei Gong, Wei Gong, Wei Gong, Wei Gong, Lu Xu, Chenxi Liu

“…LiDAR offers unparalleled advantages in capturing complex vertical canopy structures. In this study, we used multi-source data, particularly LiDAR-derived canopy structure products, to analyze the annual variations in canopy structural parameters and GPP/SIF across different forest types, investigate the response of canopy structure to the GPP-SIF relationship, and employ machine learning models to estimate GPP and assess the contribution of canopy structural factors. …”
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Genetically predicted brain cortical structure mediates the causality between insulin resistance and cognitive impairment by Chaojuan Huang, Yuyang Zhang, Mingxu Li, Qiuju Gong, Siqi Yu, Zhiwei Li, Mengmeng Ren, Xia Zhou, Xiaoqun Zhu, Zhongwu Sun

“…Our investigation aims to establish the causal relationship and direction between insulin resistance and cognition, while also quantifying the mediating role of brain cortical structure in this association.MethodsThe publicly available data sources for insulin resistance (fasting insulin, homeostasis model assessment beta-cell function and homeostasis model assessment insulin resistance, proinsulin), brain cortical structure, and cognitive phenotypes (visual memory, reaction time) were obtained from the MAGIC, ENIGMA, and UK Biobank datasets, respectively. …”
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Observed upper-ocean structure and seasonal production in the southern Kerguelen Plateau region, 1994-2021 by Man Liang, Annie Foppert, Annie Foppert, Karen J. Westwood, Karen J. Westwood, Sophie Bestley, Sophie Bestley

“…We collate ship-based hydrographic data on the vertical structure of the upper water column near 80°E from eight voyages spanning 1994 to 2021, from 58°S towards the Antarctic continent. …”
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Sequence-structure based prediction of pathogenicity for amino acid substitutions in proteins associated with primary immunodeficiencies by Ekaterina S. Porfireva, Anton D. Zadorozhny, Anastasia V. Rudik, Dmitry A. Filimonov, Alexey A. Lagunin, Alexey A. Lagunin

“…In this study, we have developed classification sequence-structure-property relationships (SSPR) models for predicting the pathogenicity of amino acid substitutions (AAS) in 25 proteins associated with the most important and genetically studied PIDs and encoded genes: IL2RG, JAK3, RAG1, RAG2, ADA, DCLRE1C, CD40LG, WAS, ATM, STAT3, KMT2D, BTK, FOXP3, AIRE, FAS, ELANE, ITGB2, CYBB, G6PD, GATA2, STAT1, IFIH1, NLRP3, MEFV, and SERPING1.MethodsThe data on 4825 pathogenic and benign AASs in the selected proteins were extracted from ClinVar and gnomAD. …”
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Morphological Evaluation of Infraorbital Canal and its Relation with Surrounding Structures Utilising CBCT: An Observational Study by Janeswari Lokam, Jyothirmai koneru, Reddy Sudhakara Reddy, Ramesh Tatapudi, Bhargavi Chinnamurthy, Ramesh kumar Budumuru

“…Aim: To analyse and determine the morphometric variations of the infraorbital canal and its association with nearby structures utilising Cone Beam Computed Tomography (CBCT). …”
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Evolution of the Structure of Double-Layer Technology Cooperation-Transfer Networks and Its Impact on Innovation Capabilities by Chen Yuling, Xing Hexiang, Du Debin

“…Therefore, this study constructed a double-layer innovation network for the Yangtze River Delta for the period 2010 to 2019 based on patent collaboration and transfer data. It characterizes the basic evolutionary features of this double-layer network, analyzes the structural development differences between the collaboration and transfer subnetworks, investigates the dynamics of their coupling evolution, and explores the spatial spillover effects of the dual-layer network structure on urban innovation capacity. …”
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Cardiometabolic state links neurovascular burden with brain structure and function: Evidence from EEG and MRI by Daniel Franco-O’Byrne, Ana M. Castro-Laguardia, Carolina Delgado, James M. Shine, David Huepe, Raul González-Gomez, Enzo Tagliazucchi, Cecilia Gonzalez-Campo, Agustín Ibañez, Vicente Medel

“…Aging affects brain structure and function alongside metabolic and vascular processes leading to energetic impairments. …”
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Role of air pollution exposure in the alteration of brain cortical structure: A Mendelian randomization study by Chaojuan Huang, Zimei Cheng, Xu Wu, Zhiwei Li, Mingxu Li, Xingliang Feng, Yuyang Zhang, Qian Zhao

“…Conclusions: Our exploration established causal relationships between air pollution exposure and brain cortical structure, underscoring the significance of mitigating air pollution to preserve brain cortical morphology.…”
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Systematic Bias in Ionizing Radiation Escape Fraction Measurements from Foreground Large-scale Structures by Claudia M. Scarlata, Wanjia Hu, Matthew J. Hayes, S. Taamoli, Ali A. Khostovan, C. M. Casey, Andreas L. Faisst, Jeyhan S. Kartaltepe, Yu-Heng Lin, Mara Salvato, Marc Rafelski

“…This emphasizes the need to account for the large-scale structure of the IGM in analyses of ionizing radiation escape fractions and highlights the advantages of a photometric approach for increasing the number of sampled lines of sight across large fields. …”
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Phylogenetic Structure Shifts Across Life-History Stages in Response to Microtopography and Competition in Subtropical Forests by Weiqi Meng, Haonan Zhang, Lianhao Sun, Jianing Xu, Yajun Qiao, Haidong Li

“…This study focuses on a subtropical evergreen broad-leaved forest in China, utilizing a large permanent plot established in the Yaoluoping National Nature Reserve. By integrating data from a full-stem census and total station surveying, we analyzed the phylogenetic structure of the plant community as a whole and across different life-history stages (saplings, juveniles, and adults) while quantitatively assessing microtopographic variables and an interspecific competition index. …”
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Re-Os age of molybdenite from the Hannivka deposit, Kryvyi Rih structure, Ukrainian Shield by Yu. Ye. Khomych, V. V. Sukach, L. V. Shumlyanskyy, S. M. Bondarenko, V. O. Syomka, S. Tessalina, M. M. Reshetnyk

“…The model age for sample 3219/189.5 from Serhiivka is 3013 ± 17 Ma, which is in good agreement with previously obtained data 3.0–3.1 Ga for the Serhiivka mineralization using Re–Os method. …”
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Considerations for Establishing a Behavioral Policy-Making and Nudge Institution within the Country's Executive Structure by Seyed Kamal Vaezi, Maryam Darbandi

“…Through this rigorous interview process, a wealth of qualitative data was gathered to assess both the potential and the challenges associated with forming a dedicated behavioral insight institution.ResultsThe literature review summarizes the experiences of countries with behavioral insight teams, presenting them in three areas: operational goals and tasks, institutional and organizational structure, and legal frameworks. …”
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