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Front Cover: Generation of Molecular Counterfactuals for Explainable Machine Learning Based on Core-Substituent Recombination (ChemMedChem 3/2024)

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ChemMedChem 2024年第3期19卷

作者： Alec Lamens Prof. Jürgen Bajorath Department of Life Science Informatics and Data Science B-IT LIMES Program Unit Chemical Biology and Medicinal Chemistry Rheinische Friedrich-Wilhelms-Universität Friedrich-Hirzebruch-Allee 5/6 53115 Bonn Germany Lamarr Institute for Machine Learning and Artificial Intelligence Rheinische Friedrich-Wilhelms-Universität Bonn Friedrich-Hirzebruch-Allee 5/6 53115 Bonn Germany

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Electronic Near Point of Convergence: A Tool to Aid the Assessment of Concussion

Electronic Near Point of Convergence: A Tool to Aid the Asse...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Bo Liang Leslie S. Prichep Saloni Kanakia Jeffrey J. Bazarian Tracey Covassin Robert J. Elbin Gillian A. Hotz Jeb F. Struder Rubén Armañanzas R&D Department BrainScope Company Inc. Chevy Chase MD USA Department of Emergency Medicine University of Rochester School of Medicine Rochester NY USA Department of Kinesiology Michigan State University East Lansing MI USA Office Sports Concussion Research University of Arkansas Fayetteville AR USA UHealth Concussion Program University of Miami Miami FL USA Korey Stringer Institute University of Connecticut CT USA Institute of Data Science and Artificial Intelligence TECNUN School of Engineering University of Navarra Pamplona Spain

Near Point of Convergence (NPC) is a widely used test when assessing oculomotor dysfunction in patients with mild Traumatic Brain Injury (mTBI) or concussion. A new electronic version of the Near Point Convergence test (eNPC) was developed to automatically measure NPC distance, addressing the need to improve the administration and precision of NPC testing. Age-adjusted normative values were achieved by using goodness-of-fit and generalized linear regression models. Target subjects included males and females aged 13 to 50 years. Normative values were computed as a function of age for records from 230 healthy volunteers. eNPC values from an independent cohort of 237 patients clinically deemed to have concussion and 245 matched controls were transformed into z-scores relative to age-expected normal eNPC values and then compared to demonstrate performance in a clinical population. Mean differences between matched controls and concussed patients showed a highly significant difference for eNPC z-scores between groups. The maximum Odds-Ratio (OR) value for z-scores was reached in the cutoff interval 0.75 to 1 with a mean of 2.614 and a median of 2.627. Usability for the eNPC test was high with a rate of obtaining measurements between 92% and 98%. Using z-scores helped reduce variance of the measurement and accounted for the effect of age. Significant separation between concussed patients and matched controls validated the use of the eNPC mathematical model. Further, high OR values using z-scores demonstrated potential improved clinical utility of the eNPC in the prediction of oculomotor dysfunction.

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A robust multiplex-DIA workflow profiles protein turnover regulations associated with cisplatin resistance and aneuploidy

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Nature Communications 2025年第1期16卷 1-18页

作者： Salovska, Barbora Li, Wenxue Bernhardt, Oliver M. Germain, Pierre-Luc Wang, Qinyue Gandhi, Tejas Reiter, Lukas Liu, Yansheng Department of Pharmacology Yale University School of Medicine New Haven CT United States Cancer Biology Institute Yale University School of Medicine West Haven CT United States Biognosys AG Zurich‐Schlieren Switzerland Institute for Neuroscience Department of Health Sciences and Technology ETH Zurich Zurich Switzerland Master Program of Public Health Department of Chronic Disease Epidemiology Yale School of Public Health New Haven CT United States Department of Biomedical Informatics & Data Science Yale University School of Medicine New Haven CT United States

Quantifying protein turnover is fundamental to understanding cellular processes and advancing drug discovery. Multiplex-DIA mass spectrometry (MS), combined with dynamic SILAC labeling (pulse-SILAC, or pSILAC) reliably measures protein turnover and degradation kinetics. Previous multiplex-DIA-MS workflows have employed various strategies including leveraging the highest isotopic labeling channels to enhance the detection of isotopic signal pairs. Here we present a robust workflow that integrates a machine learning algorithm and channel-specific statistical filtering, enabling dynamic adaptation to channel ratio changes across multiplexed experiments and enhancing both coverage and accuracy of protein turnover profiling. We also introduce KdeggeR, a data analysis tool optimized for pSILAC-DIA experiments, which determines and visualizes peptide and protein degradation profiles. Our workflow is broadly applicable, as demonstrated on 2-channel and 3-channel DIA datasets and across two MS platforms. Applying this framework to an aneuploid cancer cell model before and after cisplatin resistance, we uncover strong proteome buffering of key protein complex subunits encoded by the aneuploid genome mediated by protein degradation. We identify resistance-associated turnover signatures, including mitochondrial metabolic adaptation via accelerated degradation of respiratory complexes I and IV. Our approach provides a powerful platform for high-throughput, quantitative analysis of proteome dynamics and stability in health and disease. © The Author(s) 2025.

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Mapping Emergency Medicine data to the Observational Medical Outcomes Partnership Common data Model: A Gap Analysis of the American College of Emergency Physicians Clinical Emergency data Registry

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JACEP Open 2025年第1期6卷 100016-100016页

作者： Cohen, Inessa Diao, Zihan Goyal, Pawan Gupta, Aarti Hawk, Kathryn Malcom, Bill Malicki, Caitlin Sharma, Dhruv Sweeney, Brian Weiner, Scott G. Venkatesh, Arjun Taylor, R. Andrew Department of Emergency Medicine Yale School of Medicine New Haven CT United States Section for Biomedical Informatics and Data Science Yale University School of Medicine New Haven CT United States Program of Computational Biology and Bioinformatics Yale University New Haven CT United States American College of Emergency Physicians Washington DC United States Department of Emergency Medicine Brigham and Women's Hospital Boston MA United States Center for Outcomes Research and Evaluation (CORE) Section of Cardiovascular Medicine Yale School of Medicine New Haven CT United States

Objectives: This study aims to conduct a gap analysis to determine the feasibility of mapping electronic health record data from the Clinical Emergency data Registry (CEDR) to the Observational Medical Outcomes Partnership Common data Model (OMOP-CDM). Methods: We employed a structured approach using a custom-built comparison matrix. This matrix facilitated the alignment of CEDR data fields with the corresponding elements in the OMOP-CDM schema. Each field was evaluated for compatibility, with categorization into 3 distinct types: direct matches, fields requiring transformation, and fields with no OMOP-CDM equivalent. The mapping process was informed by consultations with the Observational Health data sciences and Informatics community forums and was guided by existing documentation and best practices in data harmonization. We performed descriptive analyses, quantifying the extent of direct matches and identifying the specific transformations needed for each CEDR-CDM field to ensure compliance with the OMOP-CDM model. Results: Our analysis indicates a high degree of compatibility between CEDR and OMOP, with over 90% (244/269) of CEDR fields being successfully mapped. Specifically, 173 fields had direct matches, whereas 71 required transformations. Challenges identified include addressing fields unique to CEDR with no OMOP-CDM equivalent and managing the transformations required for proper alignment. Conclusion: The OMOP-CDM presents a promising framework for standardizing emergency medicine data, thereby enhancing future query automation, analytics, and cross-institutional collaboration. Despite the potential challenges in capturing unique CEDR fields and addressing necessary transformations, most emergency department data can be standardized within the OMOP-CDM, fostering broader insights and applications in research and public health. © 2024 The Author(s)

关键词： databases electronic health records emergency service informatics opioid/adverse effects quality of health care registries

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Modeling the number of confirmed cases of COVID-19 in East Java using negative binomial regression based on least square spline estimator

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AIP Conference Proceedings 2024年第1期3083卷

作者： Arip Ramadan Nur Chamidah I. Nyoman Budiantara Student of Doctoral Study Program of Mathematics and Natural Sciences Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia. Department of Information System School of Industrial and System Engineering Telkom University Surabaya 60231 Indonesia. Department of Mathematics Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia. Research Group of Statistical Modeling in Life Science Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia. Department of Statistics Faculty of Sciences and Data Analytics Sepuluh Nopember Institute of Technology Surabaya 60111 Indonesia.

The East Java Province has experienced a significant surge in number of confirmed cases of COVID-19. This study endeavors to investigate the potential correlation between weather conditions and the incidence of number of confirmed cases of COVID-19 in East Java. To achieve this, a nonparametric regression model, specifically, the Negative Binomial Regression (NBR) model based on the least squares spline estimator, was utilized. The outcomes of the study indicate that the Mean Absolute Percentage Error (MAPE) of nonparametic regression model is 0.30. Meanwhile, the MAPE for the parametric regression model is 0.34. The results show that a nonparametric regression model approach is better than parametric regression model approach. The study establishes that the truncated spline estimator based NBR model represents the best fit, with an MLCV value of -256.71. The findings of the study suggest that a temperature less than 21.75°C is associated with a decrease of 13.28 number of confirmed cases of COVID-19 per each 1°C increase, while a temperature between 21.75°C and 25.78°C is linked to an increase of 6.85 number of confirmed cases of COVID-19 per each 1°C increase. In contrast, a temperature greater than 25.78°C is associated with a decrease of 139.42 number of confirmed cases of COVID-19 per each 1°C increase. Similarly, a wind speed less than 5.57 m/s is related to a decrease of 12.99 number of confirmed cases of COVID-19 per each 1 m/s increase, whereas a wind speed between 5.57 m/s and 8.99 m/s is associated with a decrease of 10.29 number of confirmed cases of COVID-19 per each 1 m/s increase. Furthermore, a wind speed greater than 8.99 m/s is linked to a decrease of 19.16 number of confirmed cases of COVID-19 per each 1 m/s increase. The study provides evidence that higher temperatures and wind speeds result in a slower rise in the incidence of the number of confirmed cases of COVID-19. Consequently, it is recommended that the local government remains vigilant du

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Correction to: Multiplexed inhibition of immunosuppressive genes with Cas13d for combinatorial cancer immunotherapy (Nature Biotechnology, (2025), 10.1038/s41587-024-02535-2)

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Nature Biotechnology 2025年

作者： Zhang, Feifei Chow, Ryan D. He, Emily Dong, Chuanpeng Xin, Shan Mirza, Daniyal Feng, Yanzhi Tian, Xiaolong Verma, Nipun Majety, Medha Zhang, Yueqi Wang, Guangchuan Chen, Sidi Department of Genetics Yale University School of Medicine New HavenCT United States System Biology Institute Yale University West HavenCT United States Center for Cancer Systems Biology Yale University West HavenCT United States M.D.–Ph.D. Program Yale University West HavenCT United States Molecular Cell Biology Genetics and Development Program Yale University New HavenCT United States Yale College New HavenCT United States Immunobiology Program Yale University New HavenCT United States Department of Therapeutic Radiology Yale University School of Medicine New HavenCT United States Department of Neurosurgery Yale University School of Medicine New HavenCT United States Yale Comprehensive Cancer Center Yale University School of Medicine New HavenCT United States Yale Stem Cell Center Yale University School of Medicine New HavenCT United States Yale Center for Biomedical Data Science Yale University School of Medicine New HavenCT United States Key Laboratory of Multi-Cell Systems Shanghai Institute of Biochemistry and Cell Biology Center for Excellence in Molecular Cell Science Chinese Academy of Sciences Shanghai China

Correction to: Nature Biotechnologyhttps://***/10.1038/s41587-024-02535-2, published online 16 January 2025. In the version of the article initially published, Sidi Chen was incorrectly associated with a present address. This has now been corrected in the HTML and PDF versions of the article. © The Author(s), under exclusive licence to Springer Nature America, Inc. 2025.

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Prognostic and therapeutic value of LSM5 gene in human brain cancer Glioma: An omics database exploration approach

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Informatics in Medicine Unlocked 2022年 34卷

作者： Ullah, Md. Asad Alam, Sayka Farzana, Maisha Tayab Moin, Abu Binte Sayed Prapty, Chowdhury Nusaiba Zohora, Umme Salma Rahman, Mohammad Shahedur Department of Biotechnology and Genetic Engineering Faculty of Biological Sciences Jahangirnagar University Dhaka Bangladesh Biotechnology Program Department of Mathematics and Natural Sciences School of Data and Sciences BRAC University Dhaka Bangladesh Department of Genetic Engineering and Biotechnology Faculty of Biological Sciences University of Chittagong Chattogram Bangladesh Wazed Miah Science Research Center Jahangirnagar University Dhaka Bangladesh

This study explored the diagnostic and therapeutic values of the LSM5 gene in two commonest types of gliomas, i.e., lower-grade glioma (LGG) and glioblastoma multiforme (GBM) by exploiting a bioinformatics-based database mining pipeline. LSM5 gene was reported to be upregulated at both mRNA and protein levels in both LGG and GBM tissues compared to adjacent normal tissues. Moreover, overexpression of LSM5 was later observed to be linked with glioma patients' demographic status and advancing cancer stages. Additionally, a differential and distinct methylation pattern of the LSM5 promoter and coding sequence in glioma tissues was reported. The gene of our interest was also discovered to undergo multiple amplification events (frequency of alteration: 1.1%) in both LGG and GBM patients. Furthermore, LSM5 overexpression was reported to be correlated with the poor overall and relapse-free survival of glioma patients. Subsequently, the immune phenotype analysis revealed that the expression of LSM5 correlates with the abundance levels of various immune cells i.e., B cell, T cell, dendritic cell, and immunomodulators, i.e., IL10RB, CD48, CD274 in glioma microenvironment. Finally, functional enrichment analysis of the neighbor genes of LSM5 showed that most of the genes are involved in different pivotal cellular processes like RNA splicing, DNA mismatch repair, and DNA replication. Overall, this study suggests that LSM5 and its downstream products are potential candidates for glioma diagnosis and treatment. © 2022

关键词： Biomarker Diagnosis Glioma LSM5 Treatment

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A growth model for water distribution networks with loops

arXiv

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arXiv 2021年

作者： Sugishita, Kashin Abdel-Mottaleb, Noha Zhang, Qiong Masuda, Naoki Department of Mathematics State University of New York at Buffalo BuffaloNY14260-2900 United States Department of Transdisciplinary Science and Engineering Tokyo Institute of Technology Tokyo152-8550 Japan Department of Civil and Environmental Engineering University of South Florida TampaFL33620 United States Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo BuffaloNY14260-5030 United States Faculty of Science and Engineering Waseda University Tokyo169-8555 Japan

Water distribution networks (WDNs) expand their service areas over time. These growth dynamics are poorly understood. One facet of WDNs is that they have loops in general, and closing loops may be a functionally important process for enhancing their robustness and efficiency. We propose a growth model for WDNs which generates networks with loops and is applicable to networks with multiple water sources. We apply the proposed model to four empirical WDNs to show that it produces networks whose structure is similar to that of the empirical WDNs. The comparison between the empirical and modeled WDNs suggests that the empirical WDNs may realize a reasonable balance between cost, efficiency, and robustness in terms of the network structure. We also study the design of pipe diameters based on a biological positive feedback mechanism. Specifically, we apply a model inspired by Physarum polycephalum to find moderate positive correlations between the empirical and modeled pipe diameters. The difference between the empirical and modeled pipe diameters suggests that we may be able to improve the performance of WDNs by following organizing principles of biological flow networks. Copyright © 2021, The Authors. All rights reserved.

关键词： Water distribution systems

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Deeplenstronomy: A dataset simulation package for strong gravitational lensing

arXiv

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arXiv 2021年

作者： Morgan, Robert Nord, Brian Birrer, Simon Lin, Joshua Yao-Yu Poh, Jason University of Wisconsin-Madison United States Legacy Survey of Space and Time Data Science Fellowship Program United States Fermi National Accelerator Laboratory United States University of Chicago United States Stanford University United States University of Illinois Urbana-Champaign United States

deeplenstronomy generates SL datasets by organizing and expediting user interaction with lenstronomy. The user creates a single yaml-style configuration file that describes the aspects of the dataset: number of images, properties of the telescope and camera, cosmological parameters, observing conditions, properties of the physical objects, and geometry of the SL systems. deeplenstronomy parses the configuration file and generates the dataset, producing both the images and the parameters that led to the production of each image as outputs. The configuration files can easily be shared, enabling users to easily reproduce each other's training datasets. The premier objective of deeplenstronomy is to help astronomers make their training datasets as realistic as possible. To that end, deeplenstronomy contains built-in features for the following functionalities: use any stellar light profile or mass profile in lenstronomy;simulate a variety of astronomical systems such as single galaxies, foreground stars, galaxy clusters, supernovae, and kilonovae, as well as any combination of those systems;fully control the placements of objects in the simulations;use observing conditions of real astronomical surveys;draw any parameter from any probability distribution;introduce any correlation;and incorporate real images into the simulation. Furthermore, deeplens tronomy facilitates realistic time-domain studies by providing access to public spectral energy distributions of observed supernovae and kilonovae and incorporating the transient objects into time series of simulated images. Finally, deeplenstronomy provides data visualization functions to enable users to inspect their simulation outputs. These features and the path from configuration file to full data set are shown in Figure 1. deeplenstronomy makes use of multiple open-source software packages: lenstronomy is used for all gravitational lensing calculations and image simulation;numpy (Harris et al. 2020) Arrays are used inter

关键词： Supernovae

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Fabrication of colorless phosphate glass doped with Bi₂O₃ for lead-free radiation shielding in X-Rayand gamma-rays medical applications: A study using PHITS Monte Carlo simulation and experimental analysis

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Radiation Physics and Chemistry 2025年 237卷

作者： Ornketphon, O. Kaewjaeng, S. Meejitpaisan, P. Jumpee, C. Yabsantia, S. Chusin, T. Chaiphaksa, W. Kim, H.J. Kaewkhao, J. Department of Radiologic Technology Faculty of Associated Medical Sciences Chiang Mai University Chiang Mai 50200 Thailand Center of Radiation Research and Medical Imaging Department of Radiologic Technology Faculty of Associated Medical Sciences Chiang Mai University Chiang Mai 50200 Thailand Physics Program Faculty of Science and Technology Nakhon Pathom Rajabhat University Nakhon Pathom 73000 Thailand Center of Excellence in Glass Technology and Materials Science (CEGM) Nakhon Pathom Rajabhat University Nakhon Pathom 73000 Thailand Department of Radiologic Technology Faculty of Allied Health Sciences Naresuan University Phitsanulok 65000 Thailand Interdisciplinary Health and Data Sciences Research Unit Faculty of Allied Health Sciences Naresuan University Phitsanulok 65000 Thailand Department of Physics Kyungpook National University Daegu 41566 South Korea

In this study, glasses with the composition (65–x)P2O5–5CaF2–10NaF–10KF–10AlF3–xBi2O3 (x = 0, 5, 10, 15 mol%) were synthesized using a conventional melt-quenching technique followed by melting at 1200 °C fo... 详细信息

In this study, glasses with the composition (65–x)P₂O₅–5CaF₂–10NaF–10KF–10AlF₃–xBi₂O₃ (x = 0, 5, 10, 15 mol%) were synthesized using a conventional melt-quenching technique followed by melting at 1200 °C for 3 hrsand annealing 500 °C for 3 hrs, aimed at photon shielding applications. The resulting glasses remained transparent and colorless glasses, with increasing of Bi₂O₃ concentrations. Radiation shielding parameters (linear attenuation coefficient (μ), mass attenuation coefficients (μ_m), effective atomic number (Z_eff), effective electron density (N_eff), and half-value layer (HVL)) with increasing of Bi₂O₃ concentrations in glasses were studied using gamma and X-ray sources. Using gamma sources, the μ_m, Z_eff, and N_eff increased, while HVL decreased. X-ray shielding performance showed that as the μ_m increased, the HVL decreased. As the Bi₂O₃ concentrations increase, the concentration at 15 mol% of Bi₂O₃ has shown the best radiation shielding performance when compared to standard materials at 120 kVp. Consequently, the concentration at 15 mol% of Bi₂O₃ in glass systems are promising candidates for radiation shielding materials innovation in future. © 2025

关键词： Gamma ray Monte Carlo simulation Radiation innovation Radiation shielding X-ray

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