Detection of fusion events by RNA sequencing in FFPE versus freshly frozen colorectal cancer tissue samples by Maxim Sorokin, Maxim Sorokin, Maxim Sorokin, Maxim Sorokin, Vladimir Lyadov, Vladimir Lyadov, Vladimir Lyadov, Maria Suntsova, Marat Garipov, Anna Semenova, Natalia Popova, Egor Guguchkin, Rustam Heydarov, Marianna Zolotovskaia, Xiaowen Zhao, Qing Yan, Ye Wang, Evgeny Karpulevich, Anton Buzdin, Anton Buzdin, Anton Buzdin, Anton Buzdin

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Effects of typical plant growth regulator chlormequat chloride on alkaloidal compounds in Corydalis yanhusuo and molecular mechanisms by Zixuan Du, Jiayin Cao, Jie Meng, Heng Zhou, Qing Hu, Ling Li, Yun Liao, Shui Miao, Wenting Li, Shen Ji, Tongshuai Wang

“…In conclusion, this study revealed a dose-dependent effect of chlormequat chloride on C. yanhusuo and its associated molecular mechanisms as determined by omics analysis.…”
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Novel predictive biomarkers for atonic postpartum hemorrhage as explored by proteomics and metabolomics by Jiangxue Qu, Hai Jiang, Huifeng Shi, Nana Huang, Jiawen Su, Yan Zhang, Lian Chen, Yangyu Zhao

“…In this study, we aimed to screen for potential predictive biomarkers for atonic PPH using combined omics approaches. Methods Collection of cervicovaginal fluid (CVF) samples from 27 women with atonic PPH and 32 women with normal delivery was performed for metabolomic (LC-MS/MS) and proteomic (LC-MS/MS) detection and subsequent confirmation experiments in this nested case-control study. …”
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An atlas of neuropathic pain-associated molecular pathological characteristics in the mouse spinal cord by Fu-Lu Dong, Lina Yu, Pei-Da Feng, Jin-Xuan Ren, Xue-Hui Bai, Jia-Qi Lin, De-Li Cao, Yu-Tao Deng, Yan Zhang, Hui-Hui Shen, Hao Gong, Wen-Xing Sun, Dong-Qiu Chi, Yixiao Mei, Longfei Ma, Ming-Zhe Yin, Meng-Na Li, Peng-Fei Zhang, Nan Hu, Bing-Lin Zhou, Ying Liu, Xuan-Jie Zheng, Yi-Fan Chen, Da Zhong, Yuan-Xiang Tao, Min Yan, Bao-Chun Jiang

“…In addition, for the first time, we systematically exhibit “cross-talk omics” between the DRG neurons and SC dorsal horn neurons and glial cells, indicating an altered communication profile under NP conditions. …”
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Pilot study of a ketogenic diet in bipolar disorder: a process evaluation by Benjamin P. Rigby, Nicole Needham, Helen Grossi, Ivana Kamenska, Iain H. Campbell, Ben Meadowcroft, Frances Creasy, Cheryl Fisher, Pankaj Bahuguna, John Norrie, Gerard Thompson, Melissa C. Gibbs, Maja Mitchell-Grigorjeva, Ailsa McLellan, Tessa Moses, Karl Burgess, Rachel Brown, Michael J. Thrippleton, Harry Campbell, Daniel J. Smith, Sharon A. Simpson

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Integrative transcriptomic and metabolomic reveals squalene alleviating the inflammatory response and enhancing immunity of hybrid grouper (♀ Epinephelus fuscoguttatus × ♂ E. lance... by Xiaobo Yan, Simiao Pan, Xiangxiang Suo, Weibin Huang, Tao Li, Shuang Zhang, Yuanzhi Yang, Beiping Tan, Xiaohui Dong

“…Therefore, the present study was designed to use corn oil as the main lipid source to create a model of inflammation or low immunity and investigate the regulatory effect of squalene on the immunity of grouper, and to perform hepatic transcriptomic and metabolomic assays of grouper using omics technology, with the aim of providing basic data for the study of the mechanism of squalene. …”
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Multi-level analysis of gut microbiome extracellular vesicles-host interaction reveals a connection to gut-brain axis signaling by Walid Mottawea, Basit Yousuf, Salma Sultan, Tamer Ahmed, JuDong Yeo, Nico Hüttmann, Yingxi Li, Nour Elhouda Bouhlel, Hebatoallah Hassan, Xu Zhang, Zoran Minic, Riadh Hammami

“…First, we conducted a multi-omics profiling of MEVs’ contents from ex vivo and stool samples. …”
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Chromosome-level genome assembly and annotation of the gynogenetic large-scale loach (Paramisgurnus dabryanus) by Lei Zhang, Wanting Zhang, Yingyin Cheng, Yutong Fang, Xin Guan, Ao Gong, Yanxin Jiang, You Duan, Lei Huang, Waqar Younas, Yaping Wang, Mijuan Shi, Xiao-Qin Xia

“…These findings not only provide new insights into the genome structure of the large-scale loach but also establish a crucial reference point for omics studies and serve as an essential genomic resource for breeding programs in this species.…”
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Medium- to long-term health condition of patients post-COVID-19, exercise intolerance and potential mechanisms: A narrative review and perspective by Fabian Schwendinger, Denis Infanger, Debbie J Maurer, Thomas Radtke, Justin Carrard, Julia M Kröpfl, Aglaia Emmenegger, Henner Hanssen, Christoph Hauser, Udo Schwehr, Hans H Hirsch, Julijana Ivanisevic, Karoline Leuzinger, Aurélien E Martinez, Marc Maurer, Thomas Sigrist, Lukas Streese, Roland von Känel, Timo Hinrichs, Arno Schmidt-Trucksäss

“…Studies reporting blood biomarkers of disease-specific impairment and endothelial dysfunction yielded upregulated inflammation, hypercoagulability, organ and endothelial damage up to several months after infection. Omics’ scale lipid profiling studies provide preliminary evidence of alterations in several lipid subspecies, mostly during acute COVID-19, which might contribute to subsequent endothelial and cardiometabolic dysfunction. …”
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Modification and analysis of context-specific genome-scale metabolic models: methane-utilizing microbial chassis as a case study by M. A. Kulyashov, R. Hamilton, Y. Afshin, S. K. Kolmykov, T. S. Sokolova, T. M. Khlebodarova, M. G. Kalyuzhnaya, I. R. Akberdin

“…The approach was tested using -omics data collected for Methylotuvimicrobium alcaliphilum 20ZR, a prominent microbial chassis for methane capturing and valorization. …”
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Revealing the heterogeneity of treatment resistance in less‐defined subtype diffuse large B cell lymphoma patients by integrating programmed cell death patterns and liquid biopsy by Wei Hua, Jie Liu, Yue Li, Hua Yin, Hao‐Rui Shen, Jia‐Zhu Wu, Yi‐Lin Kong, Bi‐Hui Pan, Jun‐Heng Liang, Li Wang, Jian‐Yong Li, Rui Gao, Jin‐Hua Liang, Wei Xu

“…To identify robust prognostic biomarkers that can guide personalized management for less‐defined subtype DLBCL patients, we integrated multi‐omics data derived from 339 standard R‐CHOP‐treated patients diagnosed with less‐defined subtype DLBCL from three independent cohorts. …”
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scCamAge: A context-aware prediction engine for cellular age, aging-associated bioactivities, and morphometrics by Vishakha Gautam, Subhadeep Duari, Saveena Solanki, Mudit Gupta, Aayushi Mittal, Sakshi Arora, Anmol Aggarwal, Anmol Kumar Sharma, Sarthak Tyagi, Rathod Kunal Pankajbhai, Arushi Sharma, Sonam Chauhan, Shiva Satija, Suvendu Kumar, Sanjay Kumar Mohanty, Juhi Tayal, Nilesh Kumar Dixit, Debarka Sengupta, Anurag Mehta, Gaurav Ahuja

“…We present scCamAge, an advanced context-aware multimodal prediction engine that co-leverages image-based cellular spatiotemporal features at single-cell resolution alongside cellular morphometrics and aging-associated bioactivities such as genomic instability, mitochondrial dysfunction, vacuolar dynamics, reactive oxygen species levels, and epigenetic and proteasomal dysfunctions. scCamAge employed heterogeneous datasets comprising ∼1 million single yeast cells and was validated using pro-longevity drugs, genetic mutants, and stress-induced models. scCamAge also predicted a pro-longevity response in yeast cells under iterative thermal stress, confirmed using integrative omics analyses. Interestingly, scCamAge, trained solely on yeast images, without additional learning, surpasses generic models in predicting chemical and replication-induced senescence in human fibroblasts, indicating evolutionary conservation of aging-related morphometrics. …”
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iDIA-QC: AI-empowered data-independent acquisition mass spectrometry-based quality control by Huanhuan Gao, Yi Zhu, Dongxue Wang, Zongxiang Nie, He Wang, Guibin Wang, Shuang Liang, Yuting Xie, Yingying Sun, Wenhao Jiang, Zhen Dong, Liqin Qian, Xufei Wang, Mengdi Liang, Min Chen, Houqi Fang, Qiufang Zeng, Jiao Tian, Zeyu Sun, Juan Xue, Shan Li, Chen Chen, Xiang Liu, Xiaolei Lyu, Zhenchang Guo, Yingzi Qi, Ruoyu Wu, Xiaoxian Du, Tingde Tong, Fengchun Kong, Liming Han, Minghui Wang, Yang Zhao, Xinhua Dai, Fuchu He, Tiannan Guo

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Deep application of controlled-release urea increases the yield and saponin content of Panax notoginseng by regulating soil nitrate distribution by Yun-xia Su, Yun-xia Su, Yun-xia Su, Ping Zhao, Li-jie Jia, Li-jie Jia, Li-jie Jia, Yuan-feng Cao, Guan-ze Liu, Guan-ze Liu, Jun-wen Chen, Jun-wen Chen, Sheng-chao Yang, Sheng-chao Yang, Yan-li Zhou, Guang-qiang Long, Guang-qiang Long, Guang-qiang Long

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Dietary Tannic Acid Promotes Growth Performance and Resistance Against <i>Aeromonas hydrophila</i> Infection by Improving the Antioxidative Capacity and Intestinal Health in the Ch... by Liqin Ji, Yisen Shangguan, Chen Chen, Chengqing Wei, Junxian Zhu, Xiaoyou Hong, Xiaoli Liu, Xinping Zhu, Wei Li

“…Integrative analyses of two omics revealed that 2 g/kg of TA mitigated inflammation by activating the PPAR signaling pathway and regulating the lipid metabolism via multiple pathways, such as steroid biosynthesis and α-linolenic acid metabolism. …”
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APOE Christchurch enhances a disease-associated microglial response to plaque but suppresses response to tau pathology by Kristine M. Tran, Nellie E. Kwang, Claire A. Butler, Angela Gomez-Arboledas, Shimako Kawauchi, Cassandra Mar, Donna Chao, Rocio A. Barahona, Celia Da Cunha, Kate I. Tsourmas, Zechuan Shi, Shuling Wang, Sherilyn Collins, Amber Walker, Kai-Xuan Shi, Joshua A. Alcantara, Jonathan Neumann, Duc M. Duong, Nicholas T. Seyfried, Andrea J. Tenner, Frank M. LaFerla, Lindsay A. Hohsfield, Vivek Swarup, Grant R. MacGregor, Kim N. Green

“…We used immunohistochemical and biochemical analysis along with single-cell spatial omics and bulk proteomics to explore the impact of the ApoeCh variant on AD pathological development and the brain’s response to plaques and tau. …”
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Chemogenomic Screening in a Patient‐Derived 3D Fatty Liver Disease Model Reveals the CHRM1‐TRPM8 Axis as a Novel Module for Targeted Intervention by Sonia Youhanna, Aurino M. Kemas, Shane C. Wright, Yi Zhong, Britta Klumpp, Kathrin Klein, Aikaterini Motso, Maurice Michel, Nicole Ziegler, Mingmei Shang, Pierre Sabatier, Aimo Kannt, Hongda Sheng, Nuria Oliva‐Vilarnau, Florian A. Büttner, Brinton Seashore‐Ludlow, Jonas Schreiner, Maike Windbergs, Martin Cornillet, Niklas K. Björkström, Andreas J. Hülsmeier, Thorsten Hornemann, Jesper V. Olsen, Yi Wang, Roberto Gramignoli, Michael Sundström, Volker M. Lauschke

“…The model closely mirrors disease‐relevant endpoints, such as steatosis, inflammation and fibrosis, and multi‐omics analyses show excellent alignment with biopsy data from 306 MASH patients and 77 controls. …”
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Polymorphisms in immunosuppression-related genes are associated with AML by Mingying Li, Mingying Li, Jingjing Ye, Jingjing Ye, Mengyuan Chang, Mengyuan Chang, Lei Feng, Lei Feng, Tingting Liu, Tingting Liu, Di Zhang, Di Zhang, Yuyan Wu, Yuyan Wu, Yuechan Ma, Yuechan Ma, Guangqiang Meng, Guangqiang Meng, Chunyan Ji, Chunyan Ji, Tao Sun, Tao Sun

“…Despite new immunotherapeutic strategies entering standard clinical care for various tumors, progress in AML remains poor. Multi-omics analyses, such as single-cell transcriptomics, have revealed many potential new targets to improve AML prognosis from an immunological perspective.MethodsDNA from 307 AML patients and 316 healthy individuals were extracted. …”
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Targeted ErbB4 receptor activation prevents D-galactose-induced neuronal senescence via inhibiting ferroptosis pathway by Ji-Ji Dao, Ji-Ji Dao, Wei Zhang, Wei Zhang, Chong Liu, Chong Liu, Qian Li, Qian Li, Chen-Meng Qiao, Chen-Meng Qiao, Chun Cui, Chun Cui, Yan-Qin Shen, Yan-Qin Shen, Shuang-Xi Chen, Shuang-Xi Chen, Wei-Jiang Zhao, Wei-Jiang Zhao

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Comparison of differences in transcriptional and genetic profiles between intra-central nervous system and extra-central nervous system large B-cell lymphoma by Shu Wang, Hong Chen, Bo Dai, Kang Zheng, Jiajun Zheng, Yuqi Zhu, Yan Yuan, Tianling Ding, Qian Wang, Liqian Xie, Rui Feng, Fengping Zhu, Jianbin Xiang, Weiqun Ding, Hong Ding, Yuan Li, Xiaodong Gu, Kunpeng Wu, Yifan Yuan, Jianping Song, Dongxiao Zhuang, Haoshu Zhong, Hanfeng Wu, Ying Mao, Tong Chen

“…To explore its specific pathogenesis and therapeutic targets, we performed multi-omics sequencing on tumor samples from patients diagnosed with PCNS-DLBCL, secondary CNS-DLBCL or extracranial (ec) DLBCL.By single-cell RNA sequencing, highly proliferated and dark zone (DZ)-related B cell subclusters, MKI67_B1, PTTG1_B2 and BTG1_B3, were predominant significantly in PCNS-DLBCL. …”
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