Structural Stability Comparisons Between Natural and Engineered Group II Chaperonins: Are Crenarchaeal “Heat Shock” Proteins Also “pH Shock” Resistant? by Mercede Furr, Shadi A. Badiee, Sreenivasulu Basha, Shilpi Agrawal, Zeina Alraawi, Sobroney Heng, Carson Stacy, Yeasin Ahmed, Mahmoud Moradi, Thallapuranam K. S. Kumar, Ruben Michael Ceballos

“…Molecular dynamics (MD) simulations complement the wet lab data. Specifically, MD suggests that the HSPβ secondary structure is the most stable. …”
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Impact of intragastric administration of donkey milk on mouse immunity utilizing gut microbiomics and plasma metabolomics by Jianwen Wang, Jianwen Wang, Wanlu Ren, Zhiwen Sun, Shibo Liu, Zixiang Han, Yongfa Wang, Yaqi Zeng, Yaqi Zeng, Jun Meng, Jun Meng, Xinkui Yao, Xinkui Yao

“…Correlation analysis of differential metabolites and microbiomes indicated a correspondence between Falsiroseomonas and Salipiger species and the antioxidant coenzyme Q that has the potential to activate the immune system.ConclusionThe data collectively suggest that DM may adjust the murine gut microbiome and plasma metabolites thereby potentially improving immunity in mice.…”
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Global Ionospheric TEC Map Prediction Based on Multichannel ED-PredRNN by Haijun Liu, Yan Ma, Huijun Le, Liangchao Li, Rui Zhou, Jian Xiao, Weifeng Shan, Zhongxiu Wu, Yalan Li

“…The proposed Multichannel ED-PredRNN was compared with COPG, ConvLSTM, and convolutional gated recurrent unit (ConvGRU) from multiple perspectives on a data set of 6 years, including comparisons at different solar activities, time periods, latitude regions, single stations, and geomagnetic storm periods. …”
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A longan-picking sequence planning method for UAV system based on multi-target tracking by Kaixuan Wu, Meiqi Zhang, Linlin Shi, Hengxu Chen, Yuju Mai, Mingda Luo, Hengyi Lin, Jun Li

“…Field tests show that the UAV system, integrated with the proposed sequence planning model, reduces overall picking time by 5.4% (104 seconds) in orchards with varying fruit densities, validating the algorithm's effectiveness in real applications.…”
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Predicting tumor mutation burden and VHL mutation from renal cancer pathology slides with self‐supervised deep learning by Qingyuan Zheng, Xinyu Wang, Rui Yang, Junjie Fan, Jingping Yuan, Xiuheng Liu, Lei Wang, Zhuoni Xiao, Zhiyuan Chen

“…Methods We obtained whole slide images (WSIs) and somatic mutation data of 350 ccRCC patients from The Cancer Genome Atlas for developing SSL‐ABMIL model. …”
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Classification of management tools in small business organizations for developing a sales funnel by E. R. Tolstova, L. V. Silakova

“…The following problems are identified for small businesses: the issue of scaling, the need to automate workflows, collecting feedback and feedback from customers, processing applications, great competition in the market, parallelization of workflows, organization of hierarchy in the workflow. …”
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A systematic review of microsimulation models for skin cancer by Caroline G. Watts, Kirstie G. McLoughlin, Stephen Wade, Amelia K. Smit, H. Peter Soyer, Pablo Fernandez-Peñas, David C. Whiteman, Pascale Guitera, Gillian Reyes-Marcelino, Karen Canfell, Anne E. Cust, Michael Caruana

“…Limitations from these models included assuming an average tumour behaviour and constant melanoma development and progression over time. Data availability was also noted as a limitation for some models. …”
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Machine learning prediction of metabolic dysfunction-associated fatty liver disease risk in American adults using body composition: explainable analysis based on SHapley Additive e... by Yan Hong, Xinrong Chen, Ling Wang, Fan Zhang, ZiYing Zeng, Weining Xie

“…The GBM model offers robust predictive accuracy and interpretability, with potential applications in clinical decision-making and public health screening strategies. …”
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Knowledge and practice of dental professionals regarding vertical teeth preparation techniques by Nasser M. Alahmari, Mohammed A. K. Al-Haboob, Thrya S. Gadah, Nassreen H. Albar, Mohammed M. Al Moaleem, Mohammed E. Sayed, Ashraf Mohammed Alhumaidi, Taha M. A. S. Al-Amri, Shehab S. A. Diaban, Abdulrahman A. H. S. Tajedin

“…Clinical trial number Not applicable.…”
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Bridging the gap: the mediating role of self-efficacy in the impact of workload on core competencies among pediatric nurses by Abdelaziz Hendy, Rasha Kadri Ibrahim, Naglaa Hassan Abuelzahab, Amna Nagaty Aboelmagd, Hanan F. Alharbi, Nasiru Mohammed Abdullahi, Lisa Babkair, Yasir S. Alsalamah, Zainab Attia Abdallah, Waad Hasan Ali, Wesam Taher Almagharbeh

“…Clinical trial number Not applicable.…”
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General polypharmacy, psychotropic polypharmacy, attitudes of patients on psychotropic deprescribing, and associated factors in adult psychiatric outpatients: a survey study in a c... by Muluken Adela Alemu, Taklo Simeneh Yazie, Woretaw Sisay Zewdu, Liknaw Workie Limenh, Tewodros Ayalew Tessema, Tirsit Ketsela Zeleke, Getu Tesfaw Adiss, Achenef Bogale Kassie, Getaye Tessema Desta, Abrham Nigussie Assefa, Tilaye Arega Moges

“…Clinical trial number Not applicable.…”
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Near infrared reflectance spectroscopy-driven chemometric modeling for predicting key quality traits in lablab bean (Lablab purpureus L.) Germplasm by Simardeep Kaur, Naseeb Singh, Ernieca L. Nongbri, Mithra T, Veerendra Kumar Verma, Amit Kumar, Tanay Joshi, Jai Chand Rana, Rakesh Bhardwaj, Amritbir Riar

“…The models were optimized for derivatives, gap selection, and smoothing, and evaluated using independent test data and key performance metrics including coefficient of determination (R²), bias, and Residual Prediction Deviation (RPD). …”
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How health systems approached respiratory viral pandemics over time: a systematic review by Walter Ricciardi, Maria Luisa Di Pietro, Drieda Zaçe, Fidelia Cascini, Ilda Hoxhaj, Margherita Ferranti, Stefania Boccia

“…Double-blinded screening process was conducted by titles/abstracts and subsequently eligible full texts were read and pertinent data were extracted. When applicable, quality assessment was conducted for the included articles. …”
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Valorization of Anaerobic Liquid Digestates Through Membrane Processing and Struvite Recovery—The Case of Dairy Effluents by Anthoula C. Karanasiou, Charikleia K. Tsaridou, Dimitrios C. Sioutopoulos, Christos Tzioumaklis, Nikolaos Patsikas, Sotiris I. Patsios, Konstantinos V. Plakas, Anastasios J. Karabelas

“…Validation of simulator results with pilot data enables reliable predictions required for scaling up NF systems. …”
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Multi-omics exploration of the factors influencing feather coverage in laying hens by Xin Li, Xiaohui Shen, Xiaoliang Wang, Yao Yan, Wei Liu, Kai Zhan, Daqian He, Changsuo Yang, Huaxiang Yan, Junfeng Yao

“…Integration of multi-omics data demonstrated significant correlations between microbial composition and host gene expression (P < 0.05), highlighting the synergistic regulation of feather morphogenesis via microbial-metabolite crosstalk.ConclusionsThis study elucidates the intricate interplay between host genetics and gut microbiota in regulating feather coverage, providing insights into epithelial biology and potential therapeutic targets for tissue homeostasis disorders. …”
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Prioritization of Lipid Metabolism Targets for the Diagnosis and Treatment of Cardiovascular Diseases by Zhihua Wang, Shuo Chen, Fanshun Zhang, Shamil Akhmedov, Jianping Weng, Suowen Xu

“…Finally, we integrated serum proteomic data to develop a machine learning model comprising 5 proteins for disease prediction. …”
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Structured noise champagne: an empirical Bayesian algorithm for electromagnetic brain imaging with structured noise by Sanjay Ghosh, Sanjay Ghosh, Chang Cai, Ali Hashemi, Yijing Gao, Stefan Haufe, Kensuke Sekihara, Ashish Raj, Srikantan S. Nagarajan

“…Efficient reconstruction of electrophysiological activity of neurons in the brain from EEG/MEG measurements is important for neuroscience research and clinical applications. An enduring challenge in this field is the accurate inference of brain signals of interest while accounting for all sources of noise that contribute to the sensor measurements. …”
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Enhancing Genomic Prediction Accuracy with a Single-Step Genomic Best Linear Unbiased Prediction Model Integrating Genome-Wide Association Study Results by Zhixu Pang, Wannian Wang, Pu Huang, Hongzhi Zhang, Siying Zhang, Pengkun Yang, Liying Qiao, Jianhua Liu, Yangyang Pan, Kaijie Yang, Wenzhong Liu

“…The single-step GBLUP (ssGBLUP) model, which integrates pedigree, phenotypic, and genomic data, has improved genomic prediction. However, ssGBLUP assumes that all markers contribute equally to genetic variance, which can limit its predictive accuracy, especially for traits controlled by major genes. …”
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Knockdown of SLC7A5 inhibits malignant progression and attenuates oxaliplatin resistance in gastric cancer by suppressing glycolysis by Yan Zhang, Jian Cao, Zheng Yuan, Jiahui Zhou, Hao Zuo, Xinsheng Miao, Xinhua Gu

“…Methods OXARGs with prognostic value in GC were analyzed using GC oxaliplatin resistance data from the GEO and TCGA databases. RT-qPCR and WB assay were applied to verify the expression of MT2A, NOTCH1 and SLC7A5 in oxaliplatin-resistant GC cells (HGC27R and MKN45R). …”
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Divergent effects of monomethyl branched-chain fatty acids on energy metabolism and insulin signaling in human myotubes by Parmeshwar Bajirao Katare, Ragna H. Tingstad, Sivar T. Beajani, Jørgen Pasjkurov Indseth, Vibeke H. Telle-Hansen, Mari C.W. Myhrstad, Arild C. Rustan, Lars Eide, Oliwia Witczak, Vigdis Aas

“…In conclusion, the study demonstrates that different BCFAs have distinct effects on energy metabolism in myotubes, 12-MTD mainly affect glucose metabolism, while 13-MTD, 14-MHD, and 15-MHD modulated oleic acid metabolism. These data suggest that some BCFAs might have therapeutic applications by improving energy metabolism.…”
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