Reinforcing cancer immunotherapy with engineered porous hollow mycobacterium tuberculosis loaded with tumor neoantigens by Jie Jiang, Feng-Ying Huang, Shu-Zhen Dai, Guang-Hong Tan, Ming-Hui Chen, Hengyu Chen, Wu-Ping Zheng, Ri-Hong Wu, Weijing Xie

“…One approach is to stimulate antigen-presenting cells (APCs) to uptake neoantigens. Mycobacterium tuberculosis (MTb) contains pathogen-associated molecular patterns (PAMPs) recognized by APCs and adhesion molecules that facilitate MTb invasion of APCs. …”
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Relationship of monocyte to high-density lipoprotein ratio (MHR) and other inflammatory biomarkers with sarcopenia: a population-based study by Zhiwei Xue, Jian Cao, Jianhui Mou, Rui Wang, Peng Liu

“…Compared to the lowest quartile of ln MHR, higher quartiles were significantly associated with increased odds of low muscle mass (P for trend < 0.0001). In ROC analysis, ln MHR + ln SII had a higher AUC value than other indicators (AUC = 0.608). …”
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Novel models based on machine learning to predict the prognosis of metaplastic breast cancer by Yinghui Zhang, Wenxin An, Cong Wang, Xiaolei Liu, Qihong Zhang, Yue Zhang, Shaoqiang Cheng

“…Results: The CatBoost model we developed exhibits high accuracy and correctness, making it the best-performing model for predicting survival outcomes in patients with MBC (1-year AUC = 0.833, 3-year AUC = 0.806; 5-year AUC = 0.810). …”
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Optimasi Klasifikasi Sentimen Komentar Pengguna Game Bergerak Menggunakan Svm, Grid Search Dan Kombinasi N-Gram by Syahroni Wahyu Iriananda, Renaldi Widi Budiawan, Aviv Yuniar Rahman, Istiadi Istiadi

“…Kinerja model dinilai menggunakan metrik seperti Akurasi, Presisi, Recall, dan Area di Bawah Kurva ROC (AUC). Hasil menunjukkan bahwa dengan dataset gabungan (Allgame) dan integrasi fitur seleksi N-Gram Unigram, Bigram, dan Trigram (UniBiTri), model ini mencapai akurasi 87,3%, presisi 88,5%, recall 85,5%, dan AUC 0,9081, menggunakan kernel Fungsi Basis Radial (RBF) dengan validasi silang k-fold (k=10).   …”
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Invisible Scout: A Layer 2 Anomaly System for Detecting Rogue Access Point (RAP) by Diki Arisandi, Nazrul M. Ahmad, Subarmaniam Kannan

“…When tested in an open environment, the model's performance improved, achieving an AUC score of 0.952 and a CA of 0.994. Furthermore, under a de-authentication attack, the model achieved an AUC score of 0.955 and a CA of 0.996. …”
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Improving the predictive capability of Framingham Risk Score for the risk of myocardial infarction based on coronary artery calcium score in healthy Singaporeans by Ching Yee Ivory Yeo, John Carson Jr Allen, Weiting Huang, Wei Ying Tan, Siew Ching Kong, Khung Keong Yeo

“…Results: We demonstrated a significant improvement in the area under curve (AUC) of SG FRS (AUC = 0.641) after recalibration and incorporation of additional variables (fasting blood glucose and wearable-derived activity levels) (AUC = 0.774) (P < 0.001). …”
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The Relationship Between Hip Range of Motion and Pitching Kinematics Related to Increased Elbow Valgus Loads in Collegiate Baseball Pitchers: A Pilot Study by Giorgio Zeppieri Jr., Michelle L Bruner, Jon P Michelini, Kevin W Farmer

“…Inclinometer measurements were used to measure hip internal (IR), external (ER) ROM, and total rotational arc at the hip (IR + ER ROM). Correlations were used to evaluate the association between hip IR, ER, and total rotational arc ROM (TRARC) and six kinematic variables…”
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Risk of first venous thrombosis by comparing different thrombin generation assay conditions: results from the MEGA case-control study. by Kristien Winckers, Eugenia Biguzzi, Stella Thomassen, Alexandra Heinzmann, Frits R. Rosendaal, Tilman Mathias Hackeng, Astrid van Hylckama Vlieg

“…Methods: Basal TG at low tissue factor (TF) concentration and high TF concentration in the presence and absence of activated protein C (APC) were measured in plasma samples from 2,081 patients with first VTE and 2,908 healthy controls from the MEGA study. …”
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Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses by Ying Xiong, Linpeng Yao, Jinglai Lin, Jiaxi Yao, Qi Bai, Yuan Huang, Xue Zhang, Risheng Huang, Run Wang, Kang Wang, Yu Qi, Pingyi Zhu, Haoran Wang, Li Liu, Jianjun Zhou, Jianming Guo, Feng Chen, Chenchen Dai, Shuo Wang

“…The first diagnostic model designed to predict the malignancy of renal masses achieves area under the curve (AUC) of 0.871 in the prospective test set. This model surpasses the average performance of seven seasoned radiologists. …”
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Decoding the specific minty-like aroma of ‘Rucheng baimaocha’ (camellia pubescens) black tea by Jian Ouyang, Ronggang Jiang, Huimin An, Xingchang Ou, Jing Wang, He Xie, Wenjie Fu, Jing Zhang, Hongyu Chen, Qi Liu, Juan Li, Haitao Wen, Ligui Xiong, Jian-an Huang, Zhonghua Liu

“…In this study, gas chromatography-olfactometry (GC-O) combined with aroma extraction dilution analysis detected 26 aroma-active compounds (ACCs), of which 20 ACCs were quantified as odorants of RCBT infusion. …”
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Personalized prediction of glycemic responses to food in women with diet-treated gestational diabetes: the role of the gut microbiota by Polina V. Popova, Artem O. Isakov, Anastasiia N. Rusanova, Stanislav I. Sitkin, Anna D. Anopova, Elena A. Vasukova, Alexandra S. Tkachuk, Irina S. Nemikina, Elizaveta A. Stepanova, Angelina I. Eriskovskaya, Ekaterina A. Stepanova, Evgenii A. Pustozerov, Maria A. Kokina, Elena Y. Vasilieva, Lyudmila B. Vasilyeva, Soha Zgairy, Elad Rubin, Carmel Even, Sondra Turjeman, Tatiana M. Pervunina, Elena N. Grineva, Omry Koren, Evgeny V. Shlyakhto

“…Adding microbiome data increased the explained variance in peak glycemic levels (GLUmax) from 34 to 42% and in incremental area under the glycemic curve (iAUC120) from 50 to 52%. The final model showed better correlation with measured PPGRs than one based only on carbohydrate count (r = 0.72 vs. r = 0.51 for iAUC120). …”
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Biological subphenotypes in patients hospitalized with suspected infection in Thailand: a secondary analysis of a prospective observational studyResearch in context by Prapassorn Poolchanuan, Taylor D. Coston, Viriya Hantrakun, Parinya Chamnan, Gumphol Wongsuvan, Pavan K. Bhatraju, Narisara Chantratita, Direk Limmathurotsakul, T. Eoin West, Shelton W. Wright

“…A parsimonious three-biomarker model identified subphenotypes in an internal validation cohort (LBP-1: area under the receiver operating curve [AUC] 0.96, 95% CI: 0.94–0.98; LBP-2: AUC 0.77, 95% CI 0.71–0.83; LBP-3: AUC 0.99, 95% CI 0.98–1.00). …”
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Models for predicting risk of endometrial cancer: a systematic review by Bea Harris Forder, Anastasia Ardasheva, Karyna Atha, Hannah Nentwich, Roxanna Abhari, Christiana Kartsonaki

“…Abstract Background Endometrial cancer (EC) is the most prevalent gynaecological cancer in the UK with a rising incidence. …”
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Differentiation value of miR-26b for major depressive disorder, schizophrenia, generalized anxiety disorder by Lingming Kong, Xiaoli Zhu, Liyi Zhang, Shengdong Chen

“…The receiver operating characteristic (ROC) curve of miR-26b in MDD patients showed that its sensitivity and specificity for diagnosis were 0.540 and 0.830, respectively, with the area under curve (AUC) being 0.728; the ROC of miR-26b for SZ and MDD differentiation showed that its sensitivity and specificity were 0.580 and 0.710, respectively, with AUC being 0.631; the ROC of miR-26b for GAD and MDD differentiation suggested that sensitivity and specificity were 0.560 and 0.750, respectively, with AUC being 0.637. …”
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Machine learning analysis of pathological images to predict 1-year progression-free survival of immunotherapy in patients with small-cell lung cancer by Hirotaka Matsumoto, Hiroaki Akamatsu, Nobuyuki Yamamoto, Yuki Sato, Daichi Fujimoto, Yoshihiko Taniguchi, Motohiro Tamiya, Yasuhiro Koh, Junya Fukuoka, Hisashi Tanaka, Naoki Furuya, Ryota Shibaki, Tsukasa Nozawa, Akira Sano, Yuka Kitamura, Takashi Kijima, Toshihide Yokoyama, Satoru Miura, Akito Hata, Jun Sugisaka

“…The primary outcome was the mean area under the curve (AUC) of machine learning models in predicting the 1-year PFS.Results We analyzed 100,544 patches of pathological images from 78 patients. …”
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Integration of GPS and GIS in Mapping of Secondary Schools in Akure South Local Government Area of Ondo State Nigeria by H. Tata, E.P. Ojo

“…The satellite image of the study area was downloaded from Google Earth website. ArcGIS 10.1 was used for the production of the digital map while Microsoft Access 2007 was used in generating the database. …”
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Leveraging machine learning and rule extraction for enhanced transparency in emergency department length of stay prediction by Waqar A. Sulaiman, Charithea Stylianides, Andria Nikolaou, Andria Nikolaou, Zinonas Antoniou, Ioannis Constantinou, Lakis Palazis, Anna Vavlitou, Theodoros Kyprianou, Theodoros Kyprianou, Efthyvoulos Kyriacou, Antonis Kakas, Antonis Kakas, Marios S. Pattichis, Andreas S. Panayides, Constantinos S. Pattichis, Constantinos S. Pattichis

“…In the balanced dataset, GB had an AUC of 0.729, accuracy of 68.86%, sensitivity of 75.39%, and specificity of 58.59%. …”
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Engineering a promiscuous prenyltransferase for selective biosynthesis of an undescribed bioactive cannabinoid analog by Qin Yan, Yue-Gui Chen, Xiao-Wen Yang, An Wang, Xiao-Ping He, Xue Tang, Hong Hu, Kai Guo, Zong-Hua Xiao, Yan Liu, Sheng-Hong Li

“…This study introduces a fungal aromatic prenyltransferase AscC into the engineered Escherichia coli to catalyze the transfer of C5-C15 terpenoid linear precursors to olivetolic acid. …”
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BEYOND ONE PARTY STATE DOMINANCE: A REVIEW OF RECURRENT ISSUES IN NIGERIA’S FOURTH REPUBLIC by IDREES MAHMUD GANA

“…The PDP's long-standing dominance from 1999 to 2015, followed by the APC's rise, has created a political environment that marginalizes minor parties and inhibits true political competition. …”
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