Deep Proteome Coverage of Microglia Using a Streamlined Data-Independent Acquisition-Based Proteomic Workflow: Method Consideration for a Phenotypically Diverse Cell Type by Jessica Wohlfahrt, Jennifer Guergues, Stanley M. Stevens

“…To carry out their numerous functions, microglia adopt a wide range of phenotypic states. The proteomic landscape represents a more accurate molecular representation of these phenotypes; however, microglia present unique challenges for proteomic analysis. …”
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Mir-494-3p enhances aggressive phenotype of non-small cell lung cancer cells by regulating SET/I2PP2A by Yuwen Du, Taisuke Kajino, Yukako Shimada, Takashi Takahashi, Ayumu Taguchi

“…Integration of RNA sequencing analysis of NSCLC cells with miR-494-3p inhibition and a bioinformatic search of miRNA target prediction algorithms resulted in identification of SET/I2PP2A as a direct target of miR-494-3p. …”
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Clinical-exome sequencing unveils the genetic landscape of polycystic ovarian syndrome (PCOS) focusing on lean and obese phenotypes: implications for cost-effective diagnosis and p... by Shrinjana Dhar, Pritha Bhattacharjee

“…Young women in West Bengal, India, are more likely to have co-occurring PCOS, which includes estrogen resistance, leptin receptor insufficiency, folate deficiency, T2DM, and acanthosis nigricans, with obesity being a common phenotypic expression.…”
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White Matter Imaging Phenotypes Mediate the Negative Causality of Mitochondrial DNA Copy Number on Sleep Apnea: A Bidirectional Mendelian Randomization Study and Mediation Analysis by Ying Q, Wang M, Zhao Z, Wu Y, Sun C, Huang X, Zhang X, Guo J

“…Multiple testing errors were corrected using the Benjamini–Hochberg method.Results: Genetically predicted mtDNA-CN had a negative causal effect on SA (OR = 0.859, 95% CI = 0.785– 0.939, P = 3.20× 10− 4), whereas SA did not have a causal effect on mtDNA-CN (OR = 1.0056, 95% CI = 0.9954– 1.0159, P = 0.2825). …”
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Comparative Evaluation of a Dietary Fiber Mixture in an Intestinal Screening Platform and a Crossover Intervention Study by Femke P. M. Hoevenaars, Tim J. van den Broek, Boukje Eveleens Maarse, Matthijs Moerland, Ines Warnke, Hannah Eggink, Frank H. J. Schuren

“…Our study in healthy individuals demonstrates that a short-term in vitro exposure of individual microbiome samples to the fiber mixture is predictive of a long-term in vivo effect and relates to a distinct phenotypic cluster. …”
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Associations between smartphone GPS data and changes in psychological health and burden outcomes among family caregivers and patients with advanced cancer: an exploratory longitudi... by J. Nicholas Odom, Kyungmi Lee, Erin R. Harrell, Kristen Allen Watts, Avery C. Bechthold, Sally Engler, Frank Puga, Natashia Bibriescas, Arif H. Kamal, Christine S. Ritchie, George Demiris, Alexi A. Wright, Marie A. Bakitas, Andres Azuero

“…., GPS), called digital phenotyping, may afford the possibility of remotely monitoring and detecting distress and burden. …”
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Clinical and prognostic characteristics of <I>BRCA1/2</I>-associated breast cancer depending on the type of mutation: estrogen signaling pathway and secondary tumors by A. I. Stukan, A. Yu. Goryainova, R. A. Murashko, Z. K. Khachmamuk, O. Yu. Chukhray, S. D. Maksimenko, O. A. Goncharova, E. N. Imyanitov, V. A. Porkhanov

“…It is obvious that the NGS method can identify additional pathogenic mutations that predict the clinical course and indicate the possibility of personalizing therapy and the need to test relatives, including tumors with luminal phenotype and tumors of several localizations.…”
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GSDMD is a novel predictive biomarker for immunotherapy response: in the pan-cancer and single cell landscapes by Li Juan Huang, Feng Chen, Lin Chen, Shi Tong Zhan, Ming Min Liu, Jiang Dong Xiang, Qin Yi Zhang, Ye Yang

“…In organoid models, GSDMD expression influenced sensitivity to PARPi, suggesting a potential role in shaping the immune-responsive phenotype.ConclusionOur findings highlight GSDMD as a potential biomarker for predicting immunotherapy response and as a modulator of tumor-immune interactions. …”
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A predictive in vitro model of the impact of drugs with anticholinergic properties on human neuronal and astrocytic systems. by Elizabeth K Woehrling, H Rheinallt Parri, Erin H Y Tse, Eric J Hill, Ian D Maidment, G Christopher Fox, Michael D Coleman

“…We aimed to determine whether a relevant in vitro model may aid the identification of anticholinergic responses to drugs and the prediction of anticholinergic risk during polypharmacy. …”
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Genetic Analysis and Predictive Modeling of COVID-19 Severity in a Hospital-Based Patient Cohort by Iraide Alloza-Moral, Ane Aldekoa-Etxabe, Raquel Tulloch-Navarro, Ainhoa Fiat-Arriola, Carmen Mar, Eloisa Urrechaga, Cristina Ponga, Isabel Artiga-Folch, Naiara Garcia-Bediaga, Patricia Aspichueta, Cesar Martin, Aitor Zarandona-Garai, Silvia Pérez-Fernández, Eunate Arana-Arri, Juan-Carlos Triviño, Ane Uranga, Pedro-Pablo España, Koen Vandenbroeck-van-Caeckenbergh

“…In addition, we designed a multivariate predictive model including HLA, PRS and clinical data which displayed an area under the curve (AUC) value of 0.79. …”
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Identification of CCDC58 as a potential predictive biomarker of immune cell infiltration in hepatocellular carcinoma by Zishen Liu, Xiaotong Lin, Tingting Tan, Guozhu Xie, Ying Chen

“…Conclusion Our study indicated that CCDC58 might serve as a potential predictive biomarker of immune cell infiltration in HCC and is correlated with poor prognosis in HCC patients.…”
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Disseminated tumor cells in bone marrow as predictive classifiers for small cell lung cancer patients by Ying Wang, Jingying Nong, Baohua Lu, Yuan Gao, Mingming Hu, Cen Chen, Lina Zhang, Jinjing Tan, Xiaomei Yang, Peter Ping Lin, Xingsheng Hu, Tongmei Zhang

“…Conclusions: Our findings suggest that bone marrow sampling and characterization of DTC subtypes provided a valuable tool for predicting treatment response and the prognosis in SCLC. …”
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Comparisons of four cognitive-frailty measures in predicting dementia and disability by Jui-Yuan Chung, Hei-Fen Hwang, Lalu Suprawesta, Mau-Roung Lin

“…Abstract Background Several cognitive-frailty (CF) measurements, such as traditional CF, the CF phenotype, physio-cognitive decline syndrome (PCDS), and motoric cognitive risk syndrome (MCRS) have been developed but their predictive abilities for incident dementia and incident disability are seldom compared. …”
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Improved diagnostic prediction of the pathogenicity of bloodstream isolates of Staphylococcus epidermidis. by Shannon M VanAken, Duane Newton, J Scott VanEpps

“…In this study we sought to improve the diagnostic accuracy of predicting pathogenicity by focusing on phenotypic markers (i.e., antibiotic resistance, growth fitness in human plasma, and biofilm forming capacity) and the presence of specific virulence genes (i.e., mecA, ses1, and sdrF). …”
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Predicting cell morphological responses to perturbations using generative modeling by Alessandro Palma, Fabian J. Theis, Mohammad Lotfollahi

“…Abstract Advancements in high-throughput screenings enable the exploration of rich phenotypic readouts through high-content microscopy, expediting the development of phenotype-based drug discovery. …”
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Screening and Comprehensive Evaluation of Drought Resistance in Cotton Germplasm Resources at the Germination Stage by Yan Wang, Qian Huang, Li Liu, Hang Li, Xuwen Wang, Aijun Si, Yu Yu

“…The validation of the D-value prediction model based on the Best Linear Unbiased Prediction (BLUP) showed that the results obtained from two independent biological replicates were highly consistent. …”
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Computational prediction of protein interactions in single cells by proximity sequencing. by Junjie Xia, Hoang Van Phan, Luke Vistain, Mengjie Chen, Aly A Khan, Savaş Tay

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Coal and gas outburst prediction based on data augmentation and neuroevolution. by Wenbing Shi, Ji Huang, Gaoming Yang, Shuzhi Su, Shexiang Jiang

“…In constructing smart mines, predicting CGO risks efficiently and accurately is necessary. …”
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Assessing the Impact of Environment on the Color of Painted Turtles (Chrysemys picta) in the Wild by Georgina Jaimes, Erik Maki, Beth A. Reinke

“…ABSTRACT Animal coloration is a complex phenotype that may be affected by genetics, evolution, ecology, and environment. …”
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Automated pipeline for leaf spot severity scoring in peanuts using segmentation neural networks by Joshua Larsen, Jeffrey Dunne, Robert Austin, Cassondra Newman, Michael Kudenov

“…Peanut breeding programs frequently focus on developing disease-resistant peanut genotypes. However, existing phenotyping protocols employ subjective rating scales, performed by human raters, who determine the severity of leaf spot infection. …”
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