The gastric microbiome altered by A4GNT deficiency in mice by Dawei Gong, Dawei Gong, Yuqiang Gao, Rui Shi, Xiaona Xu, Mengchao Yu, Shumin Zhang, Lili Wang, Quanjiang Dong

“…The co-occurrence network appeared to be much more complex. Functional prediction demonstrated considerable decreases in the relative frequencies of functions associated with polysaccharide metabolism and transportation.ConclusionThe distinct profile in A4gnt−/− mice demonstrated a vital role of A4GNT in the establishment of the gastric microbiome. …”
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Proteomic Profiling Towards a Better Understanding of Genetic Based Muscular Diseases: The Current Picture and a Look to the Future by Marc Pauper, Andreas Hentschel, Malte Tiburcy, Sergi Beltran, Tobias Ruck, Ulrike Schara-Schmidt, Andreas Roos

“…Proteomics accelerates diagnosis and research of muscular diseases by enabling the robust analysis of proteins relevant for the manifestation of neuromuscular diseases in the following aspects: (i) evaluation of the effect of genetic variants on the corresponding protein, (ii) prediction of the underlying genetic defect based on the proteomic signature of muscle biopsies, (iii) analysis of pathophysiologies underlying different entities of muscular diseases, key for the definition of new intervention concepts, and (iv) patient stratification according to biochemical fingerprints as well as (v) monitoring the success of therapeutic interventions. …”
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Modeling the endocrine control of vitellogenin production in female rainbow trout by Kaitlin Sundling, Gheorghe Craciun, Irvin Schultz, Sharon Hook, James Nagler, Tim Cavileer, Joseph Verducci, Yushi Liu, Jonghan Kim, William Hayton

“…We anticipate that these mathematical and computational models will play an important role in future regulatory toxicity assessments and in the prediction of ecological risk.…”
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An Inflammatory Polymorphisms Risk Scoring System for the Differentiation of Ischemic Stroke Subtypes by Elena Muiño, Jurek Krupinski, Caty Carrera, Cristina Gallego-Fabrega, Joan Montaner, Israel Fernández-Cadenas

“…The genetic risk scoring system could be useful in the prediction and differentiation of ischemic stroke; however, it might be specific to particular ischemic stroke subtypes.…”
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Integration of bulk and single-cell RNA-seq reveals prognostic gene signatures in patients with bladder cancer treated with immune checkpoint inhibitors by Mina Cho, Hyun Chang, Ju Han Kim

“…This study aims to identify reliable biomarkers to enhance the prediction of treatment outcomes. Bulk RNA expression data from a BC cohort (GSE176307) receiving ICI and single-cell sequencing data from patients with BC (GSE135337) were collected. …”
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Optimization of Extraction of Compound Flavonoids from Chinese Herbal Medicines Based on Quantification Theory and Evaluation of Their Antioxidant Activity by Xu Yang, Dongli Cao, Haiyu Ji, Yingying Feng, Juan Yu, Anjun Liu

“…The result was accurate and the established prediction equation was reliable (R = 0.95). The antioxidant activity of CFs was significantly positively correlated with the concentration from 0.05 to 0.4 mg/mL. …”
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Interpretable machine learning modeling of temperature rise in a medium voltage switchgear using multiphysics CFD analysis by Mahmood Matin, Amir Dehghanian, Amir Hossein Zeinaddini, Hossein Darijani

“…SHAP analysis identified the most significant variables affecting temperature prediction as current, air velocity, duct area, and switchgear conditions, in that order.…”
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Prevalence, Awareness, Treatment, and Control of Hypertension among Chinese First-Generation Migrants and Italians in Prato, Italy: The CHIP Study by Pietro A. Modesti, Maria Calabrese, Ilaria Marzotti, Hushao Bing, Danilo Malandrino, Maria Boddi, Sergio Castellani, Dong Zhao

“…In Chinese participants, where the optimum cut-off point for body mass index was ≥23.9 kg/m2, the sensibility and specificity prediction for hypertension were 61.7% and 59.8%, respectively (area under the ROC curve = 0.629). …”
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Cognitive and Emotional Resilience in Parents with Children with Autism Spectrum Disorder During COVID-19: The Role of Promoting Variables by Aziz Sarhani-Robles, María Guillot-Valdés, María Auxiliadora Robles-Bello, David Sánchez-Teruel

“…We hypothesised that higher scores in these promoting variables would predict greater resilience, with emotional intelligence potentially serving as an underlying framework. …”
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Sodium butyrate regulates macrophage polarization by TGR5/β-arrestin2 in vitro by Miao Liu, Wen-jie Xie, Xu Zhang, Wei Wu, Guang Li, Lu Wang

“…Methods The targets of butyric acid were identified using SwissTargetPrediction database and surface plasmon resonance (SPR). …”
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The Relationship Between First-Trimester Aneuploidy Markers and Birth Weight by Cenk Soysal, Hatice Sari, Ozlem Erten, Ismail Biyik, Onur Ince, Yasemin Tasci, Nadi Keskin

“… OBJECTIVE: We aimed to determine the relationship between the first-trimester aneuploidy screeningma and the predicted weight at birth: Small for gestational age and large for gestational age. …”
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High-throughput screening of CO2 cycloaddition MOF catalyst with an explainable machine learning model by Xuefeng Bai, Yi Li, Yabo Xie, Qiancheng Chen, Xin Zhang, Jian-Rong Li

“…Among them, MOF-76(Y) achieved the top performance experimentally among reported MOFs, in good agreement with the prediction.…”
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Deciphering olfactory receptor binding mechanisms: a structural and dynamic perspective on olfactory receptors by Jingtao Wang, Jingtao Wang, Qidong Zhang, Wu Fan, Qingzhao Shi, Jian Mao, Jianping Xie, Guobi Chai, Guobi Chai, Chenglei Zhang

“…Furthermore, due to the rapid advancements in related fields such as computer simulations, the prediction and exploration of odor molecule binding to olfactory receptors have been progressively achieved through molecular dynamics simulations. …”
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Numerical and Experimental Investigation of the Effect of Cavitation on Dual Clearance Squeeze Film Damper by Zhaojun Feng, Guihuo Luo, Hai Yang, Wangqun Deng, Wei Chen, Cheng Shen

“…The film pressure distribution in the outer layer (including the positive and negative pressure zones) obtained from the experimental test agrees well with the numerical prediction, which verifies the validity of the proposed numerical model. …”
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Above dendromass estimation of juvenile Paulownia sp. by Tatiana Stankova, Veselka Gyuleva, Dimitar N. Dimitrov, Hristina Hristova, Ekaterina Andonova

“…The regression models were fitted in log-transformed form to the logarithm of the stem biomass and MM correction factor for bias was applied to the back-transformed prediction data. Two allometric relationships were derived, which adequately assess stem dendromass of young Paulownia sp. from easily measurable tree characteristics. …”
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A topology-guided high-quality solution learning framework for security-constraint unit commitment based on graph convolutional network by Liqian Gao, Lishen Wei, Shichang Cui, Jiakun Fang, Xiaomeng Ai, Wei Yao, Jinyu Wen

“…Thirdly, a customized prediction-based NS is developed to restore the feasibility of the predicted commitment. …”
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Effect of electrical stimulation with a cochlear implant on tinnitus impact: protocol of an individual patient data meta-analysis by Inge Stegeman, Adriana L Smit, Kelly Assouly

“…We will also apply prediction models to individual patient data (IPD) of clinical trials to find predictive factors of the effect of electrical stimulation on tinnitus impact.Method and analysis The IPD meta-analysis is a follow-up project of the systematic review on cochlear implantation in patients with tinnitus as a primary complaint. …”
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Optimization of Reservoir Water Quality Parameters Retrieval and Treatment Using Remote Sensing and Artificial Neural Networks by Alice Nureen Adhiambo Omondi, Yashon Ouma, Simon Njoroge Mburu, Cleophas Mecha Achisa

“…Using MLP-ANN modelling, the extracted spectral reflectance values from the selected sampling points in the reservoir were used as model inputs for the prediction of treated WQPs. A second MLP-ANN model was developed to predict the optimum coagulant dose required for raw water treatment. …”
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Optimizing Stroke Detection Using Evidential Networks and Uncertainty-Based Refinement by Faranak Akbarifar, Sean P. Dukelow, Albert Jin, Parvin Mousavi, Stephen H. Scott

“…Using deep learning methods, particularly an evidential network, we distinguished impaired participants from healthy controls while generating measures of prediction uncertainty. By retraining the network with the least uncertain samples and refining the test set by excluding the top 10% most uncertain samples, we improved the sensitivity of detecting subtle impairments in minimally impaired stroke patients (those scoring normal on the CMSA) from 0.55 to 0.75. …”
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Quantitative Structure–Activity Relationship (QSAR) Modeling of Chiral CCR2 Antagonists with a Multidimensional Space of Novel Chirality Descriptors by Ramanathan Natarajan, Ganapathy S. Natarajan, Subhash C. Basak

“…The linear regression using the principal component scores (PCSs) resulted in a three-predictor prediction model with good statistics: R² = 0.823; Adj R² = 0.790. …”
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