Safety of mycophenolate mofetil in systemic lupus erythematosus maintenance therapy: insights from the LUNA registry in a nationwide prospective cohort study by Ken-ei Sada, Shuhei Yoshida, Kenji Saito, Yuya Fujita, Eisuke Inoue, Kiyoshi Migita, Naoki Matsuoka, Hiroshi Kajiyama, Ryusuke Yoshimi, Kunihiro Ichinose, Yoshia Miyawaki, Shigeru Ohno, Nobuyuki Yajima, Yasuhiro Shimojima, Shuzo Sato, Michio Fujiwara, Keisuke Nishimura, Takashi Kida, Yuya Sumichika, Haruki Matsumoto, Jumpei Temmoku, Tomoyuki Asano, Shotaro Ogawa, Jumpei Fukita, Yusuke Matsuo, Takahisa Onishi

“…Statistical analyses employed marginal structural models with stabilised inverse probability of treatment weighting to adjust for confounders.Results The analysis included 1004 patients; the incidence of severe infections was 6.5% in the MMF group and 7.5% in the non-MMF group, with no significant difference (OR 0.69, 95% CI 0.34 to 1.39). …”
Get full text

The mediating role of physical activity avoidance in the association between weight stigma and physical activity by Po-Ching Huang, Hung-Ching Wu, Ji-Kang Chen, Xavier C.C. Fung, Nadia Bevan, Daniel Kwasi Ahorsu, Mark D. Griffiths, Jung-Sheng Chen, Kuo-Hsin Lee, Amir H. Pakpour, Chung-Ying Lin

“…Results: Structural equation modeling showed that weight-related self-stigma was significantly associated with PA avoidance (standardized coefficient [β] = 0.67, p < 0.01), and negatively associated with PA (β = −0.14, p < 0.01). …”
Get full text

Executive dysfunction relates to salience network desegregation in behavioural variant frontotemporal dementia by Melanie A. Matyi, Hamsanandini Radhakrishnan, Christopher A. Olm, Jeffrey S. Phillips, Philip A. Cook, Emma Rhodes, James C. Gee, David J. Irwin, Corey T. McMillan, Lauren Massimo

“…Given that behavioral variant frontotemporal degeneration (bvFTD) is a neurodegenerative disease associated with executive dysfunction and selective vulnerability of the salience network, we tested the hypotheses that bvFTD structural networks are de-differentiated compared to cognitively normal controls (CNC) and that network de-differentiation relates to worse executive function. …”
Get full text

Single-cell chromatin accessibility profiling reveals regulatory mechanisms and evolution in pig brains by Yue Xiang, Saixian Zhang, Yi Huang, Zhuqing Zheng, Jiahui Sun, Qiulin Zhao, Peng Zhou, Xiaolong Qi, Jingjin Li, Fuyang Xiong, Jing Xu, Shengquan Wang, Liangliang Fu, Xinyun Li

“…Abstract Background Pig brains serve as a valuable biomedical model for studying brain-related diseases due to their significant structural similarities to the human brain. Furthermore, the long-term domestication and artificial selection of domestic pigs have profoundly shaped their brains, making them an interesting subject for research. …”
Get full text

Engagement of Indigenous peoples in commercial tobacco reform strategies: a scoping review protocol by Andrew Waa, Raglan Maddox, El-Shadan Tautolo, Michelle Kennedy, Patricia Nez Henderson, Hershel Clark, Priscilla Nez, Penney Upton, Andrew Daniel Perusco, Sydney A. Martinez, Sierra Wilcox, Jeyasakthi Venugopal

“…This review supports the global goal of eradicating commercial tobacco-related harms – reframing commercial tobacco use as a structurally imposed harm sustained by colonial and commercial forces rather than personal choice. …”
Get full text

Social Determinants of Health Associated With SARS-CoV-2 Testing and Vaccine Attitudes in a Cross-Sectional Study of Latinx Individuals in Oregon by Elizabeth L. Budd, PhD, MPH, Stephanie De Anda, PhD, Sven Halvorson, MS, Leslie D. Leve, PhD, Anne Marie Mauricio, PhD, Ellen H. McWhirter, PhD, Jorge I. Ramírez García, PhD, David S. DeGarmo, PhD

“…Multilevel structural equation path modeling addressed the nonindependence of respondents nested within 52 SARS-CoV-2 testing sites across Oregon, U.S. …”
Get full text

Case Report: Phenotypic heterogeneity within an NF1 family: assessment of the pathogenicity of a de novo c.6640dupA shift mutation and a splice variant with an epilepsy phenotype by Sijing Ren, Sijing Ren, Sijing Ren, Yanling Wang, Xinhua Tong, Xiaoyu Wu, Xiaoyu Wu, Huan Yan, Huan Yan, Qing-Xia Kong, Qing-Xia Kong, Qing-Xia Kong

“…The identified genes were validated using Sanger sequencing, and alterations in the tertiary structural physicochemical properties of the mutant proteins were analyzed using AlphaFold2 bioinformatics software.ResultsWe identified two mutation sites in the NF1 gene of the patient. …”
Get full text

The relationship between educational and scientific regulatory interventions and socio-economic development in military conflict-affected countries: A Sustainable Development Goals... by Dariusz Krawczyk, Nadiia Artyukhova, Dmytro Svynarenko, Anna Vorontsova, Artem Artyukhov, Robert Rehak, Tetiana Vasylieva

“…Type of the article: Research Article AbstractThis study investigates the structural relationships between educational and scientific regulatory interventions and socio-economic development in countries affected by armed conflict and political instability, using the framework of Sustainable Development Goals (SDGs), specifically SDG 4 (Quality Education), SDG 8 (Decent Work and Economic Growth), and SDG 9 (Industry, Innovation and Infrastructure). …”
Get full text

Evaluating the long-term impact of a distance learning course on attitudes, skills, practices, and knowledge in gender-affirming healthcare among healthcare professionals in Italy by Matteo Marconi, Ughetta Maria Favazzi, Pietro Carbone, Debora Guerrera, Angela Ruocco, Martina Manoli, Martina Manoli, Cristiana Barbati, Francesca Molinaro, Federica Maria Regini, Andrea Vittozzi, Alfonso Mazzaccara, Marina Pierdominici

“…The findings underscore the need for structural support and integrated reinforcement to embed gender-affirming care into routine practice.…”
Get full text

The risk associated with ultra-processed food intake on depressive symptoms and mental health in older adults: a target trial emulation by Belayneh Mengist, Mojtaba Lotfaliany, Julie A. Pasco, Bruno Agustini, Michael Berk, Malcolm Forbes, Melissa M. Lane, Suzanne G. Orchard, Joanne Ryan, Alice J. Owen, Robyn L. Woods, John J. McNeil, Mohammadreza Mohebbi

“…We applied inverse probability treatment weighting to balance confounders. Marginal structural models were employed to estimate the population-level average effect of intervention using generalised estimated equations. …”
Get full text

Exploring key factors related to child well-being: a community-based participatory research together with children with migration background residing in socio-economically disadvan... by Louise Burenby Yxne, Louise Burenby Yxne, Rathi Ramji, Rathi Ramji, Elisabeth Mangrio, Elisabeth Mangrio, Elisabeth Mangrio, Katarina Sjögren Forss, Katarina Sjögren Forss, Therese Sterner, Therese Sterner, Margareta Rämgård, Margareta Rämgård

“…The themes covered structural aspects, such as school, healthcare and human rights, but also more personal dimensions, like close relations and the near environment, related to Bronfenbrenner’s ecological theory of human development.ConclusionThe dialogs with the children provided a deeper understanding and a holistic view of the perceptions of children with migration backgrounds residing in socio-economically disadvantaged areas regarding essential factors for their well-being. …”
Get full text

Understanding Associations Between Patient‐Level Factors and Participation in a Breast Cancer Clinical Trial by Nicole E. Caston, Luqin Deng, Courtney P. Williams, Emily B. Levitan, Andres Azuero, Russell Griffin, Karen L. Smith, Antonio C. Wolff, Michelle E. Melisko, Eileen H. Shinn, Kathleen Gallagher, Rebekah Angove, Stephanie B. Wheeler, Gabrielle B. Rocque

“…Standardized total effects (bTot) were estimated using a prespecified Structural Equation Model with 0.1, 0.3, and 0.5 indicating weak, medium, and large magnitude, respectively. …”
Get full text

Applications of Artificial Intelligence in Biotech Drug Discovery and Product Development by Yuan‐Tao Liu, Le‐Le Zhang, Zi‐Ying Jiang, Xian‐Shu Tian, Peng‐Lin Li, Pei‐Huang Wu, Wen‐Ting Du, Bo‐Yu Yuan, Chu Xie, Guo‐Long Bu, Lan‐Yi Zhong, Yan‐Lin Yang, Ting Li, Mu‐Sheng Zeng, Cong Sun

“…It highlights AI's ability to achieve >75% hit validation in virtual screening, design protein binders with sub‐Ångström structural fidelity, enhancing antibody binding affinity to the picomolar range, and optimize nanoparticles to achieve over 85% functionalization efficiency. …”
Get full text

Deep dive into hydrologic simulations at global scale: harnessing the power of deep learning and physics-informed differentiable models (<i>δ</i>HBV-globe1.0-hydroDL) by D. Feng, D. Feng, D. Feng, H. Beck, J. de Bruijn, J. de Bruijn, R. K. Sahu, Y. Satoh, Y. Wada, J. Liu, M. Pan, K. Lawson, C. Shen

“…Nevertheless, relative to LSTM, the differentiable model was hampered by structural deficiencies for cold or polar regions, highly arid regions, and basins with significant human impacts. …”
Get full text

Targeted Isolation of ω-3 Polyunsaturated Fatty Acids from the Marine Dinoflagellate <i>Prorocentrum lima</i> Using DeepSAT and LC-MS/MS and Their High Activity in Promoting Microg... by Chang-Rong Lai, Meng-Xing Jiang, Dan-Mei Tian, Wei Lu, Bin Wu, Jin-Shan Tang, Yi Zou, Song-Hui Lv, Xin-Sheng Yao

“…Through this approach, four new (<b>1</b>–<b>4</b>) and nine known (<b>5</b>–<b>13</b>) PUFA analogues were obtained from large-scale cultures of the marine dinoflagellate <i>Prorocentrum lima</i>, with lipidomic profiling identifying FA18:5 (<b>5</b>), FA18:4 (<b>7</b>), FA22:6 (<b>8</b>), and FA22:6 methyl ester (<b>11</b>) as major constituents of the algal oil extract. Structural elucidation was achieved through integrated spectroscopic analyses of IR, 1D and 2D NMR, and HR-ESI-MS data. …”
Get full text

E2F1-induced autocrine IL-6 inflammatory loop mediates cancer-immune crosstalk that predicts T cell phenotype switching and therapeutic responsiveness by Alf Spitschak, Prabir Dhar, Krishna P. Singh, Rosaely Casalegno Garduño, Shailendra K. Gupta, Shailendra K. Gupta, Julio Vera, Luca Musella, Nico Murr, Anja Stoll, Brigitte M. Pützer, Brigitte M. Pützer

“…To explore E2F1’s role in immune regulation in presence of aggressive melanoma cells, we established a coculture system and utilized transcriptome and cytokine arrays combined with bioinformatics and structural modeling. We identified an E2F1-dependent gene regulatory network with IL6 as a central hub. …”
Get full text

Newly diagnosed diseases and the frequency of their occurrence in patients after a new coronavirus infection. Results of an International Register "Dynamics Analysis of Comorbiditi... by G. P. Arutyunov, E. I. Tarlovskaya, A. G. Arutyunov, D. S. Polyakov, Yu. N. Belenkov, A. O. Konradi, Yu. M. Lopatin, A. P. Rebrov, S. N. Tereshchenko, A. I. Chesnikova, H. G. Hayrapetyan, A. P. Babin, I. G. Bakulin, N. V. Bakulina, L. A. Balykova, A. S. Blagonravova, M. V. Boldina, M. I. Butomo, A. R. Vaisberg, A. S. Galyavich, V. V. Gomonova, N. Yu. Grigoryeva, I. V. Gubareva, I. V. Demko, A. V. Evzerikhina, A. V. Zharkov, A. A. Zateishchikova, U. K. Kamilova, Z. F. Kim, T. Yu. Kuznetsova, A. N. Kulikov, N. V. Lareva, E. V. Makarova, S. V. Malchikova, S. V. Nedogoda, M. M. Petrova, I. G. Pochinka, K. V. Protasov, D. N. Protsenko, D. Yu. Ruzanov, S. A. Saiganov, A. Sh. Sarybaev, N. M. Selezneva, A. B. Sugraliev, I. V. Fomin, O. V. Khlynova, O. Yu. Chizhova, I. I. Shaposhnik, D. A. Schukarev, A. K. Abdrakhmanova, S. A. Avetisyan, H. G. Avoyan, K. K. Azaryan, G. T. Aimakhanova, D. A. Ayypova, A. Ch. Akunov, M. K. Alieva, A. R. Almukhambedova, O. Yu. Aparkina, O. R. Aruslanova, E. Yu. Ashina, O. Yu. Badina, O. Yu. Barysheva, T. I. Batluk, A. S. Batchaeva, R. A. Bashkinov, A. M. Bitieva, I. U. Bikhteev, N. A. Borodulina, M. V. Bragin, V. A. Brazhnik, A. M. Budu, G. A. Bykova, K. R. Vagapova, D. D. Varlamova, N. N. Vezikova, E. A. Verbitskaya, O. E. Vilkova, E. .A. Vinnikova, V. V. Vustina, E. A. Elena A. Galova, V. V. Genkel, D. B. Giller, E. D. Gordeychuk, E. I. Gorshenina, E. V. Grigoryeva, E. Yu. Gubareva, G. M. Dabylova, A. I. Demchenko, O. Yu. Dolgikh, M. Y. Duishobaev, D. S. Evdokimov, K. E. Egorova48, A. E. Zheldybaeva, N. V. Zarechnova, Yu. D. Zimina, S. Yu. Ivanova, E. Yu. Ivanchenko, M. V. Ilina, M. V. Kazakovtseva, E. V. Kazymova, Yu. S. Yuliya S. Kalinina, N. A. Kamardina, A. M. Karachenova, I. A. Karetnikov, N. A. Karoli, M. Kh. Karsiev, D. S. Kaskaeva, K. F. Kasymova, Zh. B. Kerimbekova, E. S. Kim, N. V. Kiseleva, D. A. Klimenko, O. V. Kovalishena, S. V. Kozlov, E. V. Kolmakova, T. P. Kolchinskaya, M. I. Kolyadich, O. V. Kondryakova, M. P. Konoval, D. Yu. Konstantinov, E. A. Konstantinova, V. A. Kordyukova, E. V. Koroleva, A. Yu. Kraposhina, T. V. Kryukova, A. S. Kuznetsova, T. Yu. Kuzmina, K. V. Kuzmichev, C. K. Kulchoroeva, T. V. Kuprina, I. M. Kuranova, L. V. Kurenkova, N. Yu. Kurchugina, N. A. Kushubakova, V. I. Levankova, A. A. Ledyaeva, T. V. Lisun, V. E. Lisyanskaya, N. A. Lyubavina, N. A. Magdeeva, K. V. Mazalov, V. I. Mayseenko, A. S. Makarova, A. M. Maripov, N. V. Markov, A. A. Marusina, E. S. Melnikov, A. I. Metlinskaya, N. B. Moiseenko, F. N. Muradova, R. G. Muradyan, Sh. N. Musaelyan, E. S. Nekaeva, N. M. Nikitina, S. E. Nifontov, E. Yu. Obolentseva, A. A. Obukhova, B. B. Ogurlieva, A. A. Odegova, Yu. V. Yuliya V. Omarova, N. A. Omurzakova, Sh. O. Ospanova, V. A/ Pavlova, E. V. Pakhomova, L. D. Petrov, S. S. Plastinina, D. A. Platonov, V. A. Pogrebetskaya, D. V. Polyakov, E. V. Ponomarenko, L. L. Popova, A. A. Potanin, N. A. Prokofieva, Yu. D. Rabik, N. A. Rakov, A. N. Rakhimov, N. A. Rozanova, S. Serikbolkyzy, Ya. A. Sidorkina, A. A. Simonov, V. V. Skachkova, R. D. Skvortsova, D. S. Skuridin, D. V. Solovieva, I. A. Solovieva, I. M. Sukhomlinova, A. G. Sushilova, D. R. Tagaeva, E. P. Tikhonova, D. S. Tokmin, A. A. Tolmacheva, M. S. Torgunakova, K. V. Trenogina, N. A. Trostyanetskaya, D. A. Trofimov, M. A. Trubnikova, A. A. Tulichev, A. T. Tursunova, N. D. Ulanova, O. V. Fatenkov, O. V. Fedorishina, T. S. Fil, I. Yu. Fomina, I. S. Fominova, I. A. Frolova, S. M. Tsvinger, V. V. Tsoma, M. B. Cholponbaeva, T. I. Chudinovskikh, I. V. Shavrin, O. A. Shevchenko, D. R. Shikhaliev, E. A. Shishkina, K. Yu. Shishkov, S. Yu Shcherbakov, G. V. Shcherbakova, E. A. Yausheva

“…Demographic, clinical, and laboratory data, computed tomography (CT) results, information about inhospital clinical course and complications of COVID-19 during hospitalization were extracted from electronic health records using a standardized data collection form. …”
Get full text

The meaning of ‘quality’ of homecare for older people: a scoping review by Alex Hall, Vanessa Davey, Lisa McGarrigle, Jayne Astbury, Kimberly Lazo Green, Nisar Ahmed, Oleta Williams, Fiona Beyer, Barbara Hanratty, Debora Price

“…We identified four dimensions: (1) relationships and continuity of care; (2) bespoke care; (3) organisational and structural aspects of care; and (4) understanding of quality as a measurable construct. …”
Get full text

NDVI Estimation Throughout the Whole Growth Period of Multi-Crops Using RGB Images and Deep Learning by Jianliang Wang, Chen Chen, Jiacheng Wang, Zhaosheng Yao, Ying Wang, Yuanyuan Zhao, Yi Sun, Fei Wu, Dongwei Han, Guanshuo Yang, Xinyu Liu, Chengming Sun, Tao Liu

“…This method leverages deep learning to capture structural changes in crop populations, optimizing conventional image features and improving NDVI estimation accuracy. …”
Get full text

Machine learning enhanced metal 3D printing: high throughput optimization and material transfer extensibility by Yuanjie Zhang, Cheng Lin, Yuan Tian, Jianbao Gao, Bo Song, Hao Zhang, Min Wang, Kechen Song, Binghui Deng, Dezhen Xue, Yonggang Yao, Yusheng Shi, Kun Kelvin Fu

“…The high throughput methodologies are mostly on obtaining the printed samples and their structural and physical properties, while ML is used for data analysis by model building for prediction (optimization), and understanding. …”
Get full text