The Association between Resolvin D1 Levels and Gestational Diabetes Mellitus: Implications for Perinatal Outcomes by Zeynep Seyhanli, Burak Bayraktar, Mevlut Bucak, Gulsan Karabay, Betul Tokgoz Cakir, Can Ozan Ulusoy, Gizem Aktemur, Selver Ozge Sefik, Serap Topkara Sucu, Sevki Celen, Ali Turhan Caglar

“…RESULTS: The plasma Resolvin D1 level in pregnant women with GDM was significantly higher compared to the control group (337±74.1 vs. 297±56.7, p<0.001). Furthermore, maternal plasma Resolvin D1 levels were associated with composite adverse neonatal outcomes [presence of at least one of the following conditions: preterm birth (<37 weeks), low birth weight (LBW) (<2500 grams), neonatal hypoglycemia, hyperbilirubinemia, APGAR score at 5th minute <7, respiratory distress syndrome (RDS), and admission to the neonatal intensive care unit (NICU)], with a cut-off of >338.75, showing a sensitivity of 56.3%, a specificity of 79.2%, and an AUC of 0.675 (95% CI: 0.567-0.771, p=0.024). …”
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Transition from Ambrisentan to Bosentan in Pulmonary Arterial Hypertension: A Single-Center Prospective Study by Su-Gang Gong, Lan Wang, Bigyan Pudasaini, Ping Yuan, Rong Jiang, Qin-Hua Zhao, Jing He, Rui Zhang, Wen-hui Wu, Jin-Ming Liu, Cai-cun Zhou

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Artificial intelligence performance in ultrasound-based lymph node diagnosis: a systematic review and meta-analysis by Xinyang Han, Jingguo Qu, Man-Lik Chui, Simon Takadiyi Gunda, Ziman Chen, Jing Qin, Ann Dorothy King, Winnie Chiu-Wing Chu, Jing Cai, Michael Tin-Cheung Ying

“…The pooled sensitivity, specificity, and DOR of ultrasound-based machine learning in classifying benign and malignant LNs were 0.836 (95% CI [0.805, 0.863]), 0.850 (95% CI [0.805, 0.886]), and 33.331 (95% CI [22.873, 48.57]), respectively, indicating no publication bias (p = 0.12). …”
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Meta-analysis of the accuracy for RASSF1A methylation in bronchial aspirates for the diagnosis of lung cancer. by Xu-Ping Chen, Shi-Xu He, Meng-You Chen, Fu-Bin Chen, Peng Wu, Ping Shi, Shi-Cai Zhao, Ling-Yan Zhao, Xiao-Min Xiong, Jia Zeng

“…The pooled results for the diagnosis of lung cancer were as follows, when compared to the pathological diagnosis: sensitivity of 0.47 (95% CI: 0.45-0.50), specificity of 0.96 (95% CI: 0.95-0.97), positive LR of 12.18 (95% CI: 8.96-16.55), negative LR of 0.56 (95% CI: 0.52-0.61), DOR of 24.05 (95% CI: 17.29-33.47), and AUC of 0.78 (Q index = 0.72), respectively. …”
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Author Correction: Synthetic augmentation of cancer cell line multi-omic datasets using unsupervised deep learning by Zhaoxiang Cai, Sofia Apolinário, Ana R. Baião, Clare Pacini, Miguel D. Sousa, Susana Vinga, Roger R. Reddel, Phillip J. Robinson, Mathew J. Garnett, Qing Zhong, Emanuel Gonçalves

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Dimensional structure of the Brief Illness Perception Questionnaire and Association with adverse childhood experiences in patients with an implantable cardioverter-defibrillator by Marc Dörner, Roland von Känel, Aju P. Pazhenkottil, Rahel Altwegg, Noelle König, Ladina Nager, Veronica Attanasio, Lisa Guth, Sina Zirngast, Anna Menzi, Claudia Zuccarella-Hackl, Mary Princip

“…Among others, a higher number of ICD shocks in the past (0.21, 95% CI = 0.01–0.41, p = 0.036), low physical activity (-2.16, 95% CI = -4.37 to -0.37, p = 0.045), more frequent ACE (0.56, 95% CI = 0.08–1.22, p = 0.030), ICD shock-related concerns (0.75, 95% CI 0.62–0.89, p < 0.001), and primary ICD indication (-2.29, 95% CI -4.47 to -0.11, p = 0.039) were significantly associated with more threatening IP. …”
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Tegaserod maleate exerts anti-tumor effects on prostate cancer via repressing sonic hedgehog signaling pathway by Maoping Cai, Shengdong Ge, Yaying Hong, Yao Chen, Yang-Zi Ren, Dacai Zhong, Mingkun Chen, Yuan Liu, Zhe-Sheng Chen, Ninghan Feng, Zhanghui Chen, Shan-Chao Zhao

“…In addition, TM suppressed the tumor growth in the cell-derived xenograft (CDX) mouse model in vivo. Mechanistically, TM exerted anti-tumor effects via downregulating GLI2, and its downtream targets, thus inhibiting the sonic hedgehog (SHH) signaling pathway. …”
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Prognostic value of inflammatory markers for all-cause mortality in patients with acute myocardial infarction in the coronary care unit: a retrospective study based on MIMIC-IV dat... by Fen Cao, Jun-jun Jiang, Gui Zhang, Jun Liu, Ping Xiao, Yang Tian, Wei Zhang, Sheng Zhang, Feng Hou, Zhong-Wu Bao, Kun Wu, Yong-zhi Zhu

“…Subsequently, subgroup analyses of gender and comorbidities were performed.Results1,386 AMI patients in the CCU were enrolled. The NLR was non-linearly and positively associated with in-hospital mortality [Q4: OR (95%CI) 2.61; (1.261–5.626), p = 0.012], 30-day mortality [Q4: OR (95%CI) 2.005; (1.048–3.925); p = 0.038], 90-day mortality [Q4: OR (95%CI) 2.191; (1.235–3.948); p = 0.008] with Q1 as the reference group. …”
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Loss of Type 2 Bone Morphogenetic Protein Receptor Activates NOD‐Like Receptor Family Protein 3/Gasdermin E‐Mediated Pyroptosis in Pulmonary Arterial Hypertension by Xiao‐ting Tian, Zhou‐yang‐fan Peng, Yu‐si Wu, Yuan‐yuan Cao, Xue‐chun Li, Ying Li, Si‐Yuan Tang, Alex F. Chen, Xiao‐hui Li

“…Moreover, BMPR2 deficiency can induce GSDME‐mediated pyroptosis through NLRP3 activation in 2 animal models, whereas activation of BMPR2 signaling by FK506 or BMP9 can reverse these phenotypes. …”
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Synthetic augmentation of cancer cell line multi-omic datasets using unsupervised deep learning by Zhaoxiang Cai, Sofia Apolinário, Ana R. Baião, Clare Pacini, Miguel D. Sousa, Susana Vinga, Roger R. Reddel, Phillip J. Robinson, Mathew J. Garnett, Qing Zhong, Emanuel Gonçalves

“…Harnessing orthogonal multi-omic information, this model successfully generates molecular and phenotypic profiles, resulting in an increase of 32.7% in the number of multi-omic profiles and thereby generating a complete DepMap for 1523 cancer cell lines. …”
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Effects of Dietary Nano-Composite of Copper and Carbon on Antioxidant Capacity, Immunity, and Cecal Microbiota of Weaned Ira White Rabbits by Ying-Huan Zhou, Xiao-Ping Liu, Xiao-Ming Gu, Hai-Xuan Lv, Yun Yang, Zai-Xing Cai, Bin Di, Chang-Kang Wang, Yu-Yun Gao, Ling Jin

“…The results showed that dietary NCCC supplementation increased the liver Cu/Zn-SOD content and up-regulated the gene expression of Cu/Zn-SOD (<i>p</i> < 0.05), while also reducing the content of MDA in the liver and enhancing the antioxidant capacity of Ira white rabbits. …”
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Direct calibration using atmospheric particles and performance evaluation of Particle Size Magnifier (PSM) 2.0 for sub-10&thinsp;nm particle measurements by Y. Liu, Y. Liu, A. Yli-Kujala, F. Schmidt-Ott, S. Holm, L. Ahonen, T. Chan, J. Enroth, J. Vanhanen, R. Cai, T. Petäjä, M. Kulmala, Y. Chen, J. Kangasluoma

“…In summary, PSM 2.0 is a powerful instrument for measuring sub-10 nm particles and can achieve more precise particle size distribution measurements with proper calibration.…”
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Liver Microbiome in Healthy Rats: The Hidden Inhabitants of Hepatocytes by Xiao Wei Sun, Hua Zhang, Xiao Zhang, Peng Fei Xin, Xue Gao, Hong Rui Li, Cai Yun Zhou, Wen Min Gao, Xuan Xuan Kou, Jian Gang Zhang

“…In the livers of six rats, we detected 54,867.50±6450.03 effective tags of the 16S rRNA gene and clustered them into 1003 kinds of operational taxonomic units (OTUs; 805.67±70.14, 729–893). …”
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Interleukin 15‐Presenting Nanovesicles with Doxorubicin‐Loaded Ferritin Cores for Cancer Immunochemotherapy by Yihui Zhai, Wen Zhang, Jinming Wang, Ying Kong, Rong Rong, Tianqun Lang, Chao Zheng, Yanke Wang, Yang Yu, Helen He Zhu, Ying Cai, Pengcheng Zhang, Yaping Li

“…Concurrently, membrane‐bound IL15c recognizes and activates IL15 receptor β/γc heterodimers, leading to a remarkable increase in the proliferation and activation of CTLs (16‐fold and 28‐fold) and NK cells (37‐fold and 50‐fold). …”
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Enhanced tumor self-targeting of lemon-derived extracellular vesicles by embedding homotypic cancer cell membranes for efficient drug delivery by Lu-Yao Yang, Guo-Wu Liang, Bing-Jie Cai, Ke-Min Xu, Yu-Jie Zhao, Xiao-Ting Xie, Yu-Lin Zhang, Chao-Qing Li, Guo-Jun Zhang

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Metals in Fishes from Yongshu Island, Southern South China Sea: Human Health Risk Assessment by Zhai Wu, Ye Xu, Minggang Cai, Sha-Yen Cheng, Huorong Chen, Dongren Huang, Kai Chen, Yan Lin, Tianyao Li, Mengyang Liu, Hengxiang Deng, Minjie Ni, Hongwei Ke

“…The concentrations of metals (mg/kg, dry weight) in these species were ND–21.60 (Cd), 1.21–4.87 (Cr), 0.42–22.4 (Cu), 1.01–51.8 (Mn), 0.30–3.28 (Ni), 6.04–1.29 × 103 (Zn), 14.89–1.40 × 103 (Fe), and 0.22–3.36 (Pb). …”
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Neuron-Specific Glycine Metabolism Links Transfer RNA Epitranscriptomic Regulation to Complex Behaviors by Jennifer Blaze, Viviana Dolores Evans, Jessica Abigail Feria Pliego, Petr Unichenko, Behnam Javidfar, Soeren Heissel, Hanan Alwaseem, Zachary Pennington, Denise Cai, Henrik Molina, Christian Henneberger, Schahram Akbarian

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In Vitro and In Situ Characterization of Fish Thymic Nurse Cells by Agust&amp;#237;n G. Zapata, Alberto J. Villena, Blanca E. Razquin, Emilio Fla&amp;#241;o, Francisco &amp;#193;lvarez, Pilar L&amp;#243;pez-Fierro

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Serum-Free Culture System for Spontaneous Human Mesenchymal Stem Cell Spheroid Formation by Guoyi Dong, Shengpeng Wang, Yuping Ge, Qiuting Deng, Qi Cao, Quanlei Wang, Zhouchun Shang, Wenjie OuYang, Jing Li, Chao Liu, Jie Tang, Weihua Zhao, Ying Gu

“…Interestingly, genes related to inflammatory response, immune response, and angiogenesis were upregulated in spheroids at day 6 and qPCR results further validated the increased expression level of related genes, including STC1, CCL7, HGF, IL24, and TGFB3. When spheroids were replated in normal FBS medium, cells formed a typical spindle-shaped morphology and FACS results showed that the recovered cells retained MSC-specific surface markers, such as CD73, CD90, and CD105. …”
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Machine learning-enhanced gesture recognition through impedance signal analysis by Huynh Hoang Nhut, Diep Quoc Tuan Nguyen, Dinh Minh Quan Cao, Tran Anh Tu, Dang Nguyen Chau, Phan Thien Luan, Tran Trung Nghia, Ching Congo Tak Shing

“…The individual accuracy values for each algorithm are as follows: KNN, 86%; GBM, 86%; NB, 84%; LR, 89%; RF, 87%; and SVM, 87%. These results emphasize the importance of impedance features in the refinement of gesture recognition. …”
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