tbuckley/cabot-search huggingface dataset:
Structures of ATP-binding cassette transporter ABCC1 reveal the molecular basis of cyclic dinucleotide cGAMP export
Authors: Omkar Shinde, Joshua A. Boyer, Stephanie Cambier, Jordyn J. VanPortfliet, Xuewu Sui, Gaya P. Yadav, Elizabeth G. Viverette, Mario J. Borgnia, A. Phillip West, Qi Zhang, Daniel B. Stetson, Pingwei Li
Journal: Immunity (2025)
How to Perform and Evaluate a Myocardial Perfusion Imaging by Computed Tomography
Authors: Saima Mushtaq, Andrea Baggiano, Francesco Cannata, Alberico Del Torto, Fabio Fazzari, Laura Fusini, Daniele Junod, Riccardo Maragna, Luigi Tassetti, Alessandra Volpe, Nazario Carrabba, Edoardo Conte, Marco Guglielmo, Lucia La Mura, Valeria Pergola, Roberto Pedrinelli, Pasquale Perrone Filardi, Andrea Igoren Guaricci, Gianluca Pontone
Journal:  (2025)

Abstract Stress computed tomography perfusion (CTP) delivers a comprehensive evaluation of both the anatomical and functional aspects in a single examination. It stands out as the only non-invasive technique capable of quantifying coronary stenosis and assessing its functional impact, offering a consolidated diagnostic and management approach for patients with confirmed or suspected coronary artery disease (CAD). This very practical review (‘How to..’ approach) provides guidance on conducting and interpreting static and dynamic CTP, along with an analysis of the strengths and limitations of these methodologies.
The TRIPOD-LLM reporting guideline for studies using large language models
Authors: Jack Gallifant, Majid Afshar, Saleem Ameen, Yindalon Aphinyanaphongs, Shan Chen, Giovanni Cacciamani, Dina Demner-Fushman, Dmitriy Dligach, Roxana Daneshjou, Chrystinne Fernandes, Lasse Hyldig Hansen, Adam Landman, Lisa Lehmann, Liam G. McCoy, Timothy Miller, Amy Moreno, Nikolaj Munch, David Restrepo, Guergana Savova, Renato Umeton, Judy Wawira Gichoya, Gary S. Collins, Karel G. M. Moons, Leo A. Celi, Danielle S. Bitterman
Journal: Nature Medicine (2025)
High-efficiency base editing in the retina in primates and human tissues
Authors: Alissa Muller, Jack Sullivan, Wibke Schwarzer, Mantian Wang, Cindy Park-Windhol, Pascal W. Hasler, Lucas Janeschitz-Kriegl, Mert Duman, Beryll Klingler, Jane Matsell, Simon Manuel Hostettler, Patricia Galliker, Yanyan Hou, Pierre Balmer, Tamás Virág, Luis Alberto Barrera, Lauren Young, Quan Xu, Dániel Péter Magda, Ferenc Kilin, Arogya Khadka, Pierre-Henri Moreau, Lyne Fellmann, Thierry Azoulay, Mathieu Quinodoz, Duygu Karademir, Juna Leppert, Alex Fratzl, Georg Kosche, Ruchi Sharma, Jair Montford, Marco Cattaneo, Mikaël Croyal, Therese Cronin, Simone Picelli, Alice Grison, Cameron S. Cowan, Ákos Kusnyerik, Philipp Anders, Magdalena Renner, Zoltán Zsolt Nagy, Arnold Szabó, Kapil Bharti, Carlo Rivolta, Hendrik P. N. Scholl, David Bryson, Giuseppe Ciaramella, Botond Roska, Bence György
Journal: Nature Medicine (2025)

Stargardt disease is a currently untreatable, inherited neurodegenerative disease that leads to macular degeneration and blindness due to loss-of-function mutations in the ABCA4 gene. We have designed a dual adeno-associated viral vector encoding a split-intein adenine base editor to correct the most common mutation in ABCA4 (c.5882G>A, p.Gly1961Glu). We optimized ABCA4 base editing in human models, including retinal organoids, induced pluripotent stem cell-derived retinal pigment epithelial (RPE) cells, as well as adult human retinal explants and RPE/choroid explants in vitro. The resulting gene therapy vectors achieved high levels of gene correction in mutation-carrying mice and in female nonhuman primates, with average editing of 75% of cones and 87% of RPE cells in vivo, which has the potential to translate to a clinical benefit. No off-target editing was detectable in human retinal explants and RPE/choroid explants. The high editing rates in primates show promise for efficient gene editing in other ocular diseases that are targetable by base editing.
Toward expert-level medical question answering with large language models
Authors: Karan Singhal, Tao Tu, Juraj Gottweis, Rory Sayres, Ellery Wulczyn, Mohamed Amin, Le Hou, Kevin Clark, Stephen R. Pfohl, Heather Cole-Lewis, Darlene Neal, Qazi Mamunur Rashid, Mike Schaekermann, Amy Wang, Dev Dash, Jonathan H. Chen, Nigam H. Shah, Sami Lachgar, Philip Andrew Mansfield, Sushant Prakash, Bradley Green, Ewa Dominowska, Blaise Agüera y Arcas, Nenad Tomašev, Yun Liu, Renee Wong, Christopher Semturs, S. Sara Mahdavi, Joelle K. Barral, Dale R. Webster, Greg S. Corrado, Yossi Matias, Shekoofeh Azizi, Alan Karthikesalingam, Vivek Natarajan
Journal: Nature Medicine (2025)

Large language models (LLMs) have shown promise in medical question answering, with Med-PaLM being the first to exceed a 'passing' score in United States Medical Licensing Examination style questions. However, challenges remain in long-form medical question answering and handling real-world workflows. Here, we present Med-PaLM 2, which bridges these gaps with a combination of base LLM improvements, medical domain fine-tuning and new strategies for improving reasoning and grounding through ensemble refinement and chain of retrieval. Med-PaLM 2 scores up to 86.5% on the MedQA dataset, improving upon Med-PaLM by over 19%, and demonstrates dramatic performance increases across MedMCQA, PubMedQA and MMLU clinical topics datasets. Our detailed human evaluations framework shows that physicians prefer Med-PaLM 2 answers to those from other physicians on eight of nine clinical axes. Med-PaLM 2 also demonstrates significant improvements over its predecessor across all evaluation metrics, particularly on new adversarial datasets designed to probe LLM limitations (P < 0.001). In a pilot study using real-world medical questions, specialists preferred Med-PaLM 2 answers to generalist physician answers 65% of the time. While specialist answers were still preferred overall, both specialists and generalists rated Med-PaLM 2 to be as safe as physician answers, demonstrating its growing potential in real-world medical applications. With an improved framework for model development and evaluation, a large language model is shown to provide answers to medical questions that are comparable or preferred with respect to those provided by human physicians.
A generalist medical language model for disease diagnosis assistance
Authors: Xiaohong Liu, Hao Liu, Guoxing Yang, Zeyu Jiang, Shuguang Cui, Zhaoze Zhang, Huan Wang, Liyuan Tao, Yongchang Sun, Zhu Song, Tianpei Hong, Jin Yang, Tianrun Gao, Jiangjiang Zhang, Xiaohu Li, Jing Zhang, Ye Sang, Zhao Yang, Kanmin Xue, Song Wu, Ping Zhang, Jian Yang, Chunli Song, Guangyu Wang
Journal: Nature Medicine (2025)
A lifespan-generalizable skull-stripping model for magnetic resonance images that leverages prior knowledge from brain atlases
Authors: Limei Wang, Yue Sun, Jakob Seidlitz, Richard A. I. Bethlehem, Aaron Alexander-Bloch, Lena Dorfschmidt, Gang Li, Jed T. Elison, Weili Lin, Li Wang
Journal: Nature Biomedical Engineering (2025)
Medical large language models are vulnerable to data-poisoning attacks
Authors: Daniel Alexander Alber, Zihao Yang, Anton Alyakin, Eunice Yang, Sumedha Rai, Aly A. Valliani, Jeff Zhang, Gabriel R. Rosenbaum, Ashley K. Amend-Thomas, David B. Kurland, Caroline M. Kremer, Alexander Eremiev, Bruck Negash, Daniel D. Wiggan, Michelle A. Nakatsuka, Karl L. Sangwon, Sean N. Neifert, Hammad A. Khan, Akshay Vinod Save, Adhith Palla, Eric A. Grin, Monika Hedman, Mustafa Nasir-Moin, Xujin Chris Liu, Lavender Yao Jiang, Michal A. Mankowski, Dorry L. Segev, Yindalon Aphinyanaphongs, Howard A. Riina, John G. Golfinos, Daniel A. Orringer, Douglas Kondziolka, Eric Karl Oermann
Journal: Nature Medicine (2025)

The adoption of large language models (LLMs) in healthcare demands a careful analysis of their potential to spread false medical knowledge. Because LLMs ingest massive volumes of data from the open Internet during training, they are potentially exposed to unverified medical knowledge that may include deliberately planted misinformation. Here, we perform a threat assessment that simulates a data-poisoning attack against The Pile, a popular dataset used for LLM development. We find that replacement of just 0.001% of training tokens with medical misinformation results in harmful models more likely to propagate medical errors. Furthermore, we discover that corrupted models match the performance of their corruption-free counterparts on open-source benchmarks routinely used to evaluate medical LLMs. Using biomedical knowledge graphs to screen medical LLM outputs, we propose a harm mitigation strategy that captures 91.9% of harmful content (F1 = 85.7%). Our algorithm provides a unique method to validate stochastically generated LLM outputs against hard-coded relationships in knowledge graphs. In view of current calls for improved data provenance and transparent LLM development, we hope to raise awareness of emergent risks from LLMs trained indiscriminately on web-scraped data, particularly in healthcare where misinformation can potentially compromise patient safety. Large language models can be manipulated to generate misinformation by poisoning of a very small percentage of the data on which they are trained, but a harm mitigation strategy using biomedical knowledge graphs can offer a method for addressing this vulnerability.
Intra-tumoral sphingobacterium multivorum promotes triple-negative breast cancer progression by suppressing tumor immunosurveillance
Authors: Zhikai Mai, Liwu Fu, Jiyan Su, Kenneth K.W. To, Chuansheng Yang, Chenglai Xia
Journal: Molecular Cancer (2025)

Intratumor-resident bacteria represent an integral component of the tumor microenvironment (TME). Microbial dysbiosis, which refers to an imbalance in the bacterial composition and bacterial metabolic activities, plays an important role in regulating breast cancer development and progression. However, the impact of specific intratumor-resident bacteria on tumor progression and their underlying mechanisms remain elusive. 16S rDNA gene sequencing was used to analyze the cancerous and paracancerous tissues from breast cancer patients. The mouse models of bearing 4T1 cell tumors were employed to assess the influence of bacterial colonization on tumor growth. Tissue infiltration of regulatory T (Treg) cells and CD8+ T cells was evaluated through immunohistochemistry and flow cytometric analysis. Comparative metabolite profiling in mice tumors was conducted using targeted metabolomics. Differential genes of tumor cells stimulated by bacteria were analyzed by transcriptomics and validated by qPCR assay. We found that Sphingobacterium displayed high abundance in cancerous tissues. Intra-tumoral colonization of Sphingobacterium multivorum (S. multivorum) promoted tumor progression in 4T1 tumor-bearing mice. Moreover, S. multivorum diminished the therapeutic efficacy of αPD-1 mAb, which was associated with the increase of regulatory T cell (Treg) infiltration, and decrese of the CD8+ T cell infiltration. Targeted metabolomics revealed a conspicuous reduction of propionylcarnitine in tumors colonized by S. multivorum Furthermore, the combination of metabolite propionylcarnitine and S. multivorum shown to suppress tumor growth compared that in S. multivorum alone in vivo. Mechanistically, S. multivorum promoted the secretion of chemokines CCL20 and CXCL8 from tumor cells. CCL20 secreted into the TME facilitated the recruitment of Treg cells and reduced CD8+ T cell infiltration, thus promoting tumor immune escape. This study reveals S. multivorum suppresses immune surveillance within the TME, thereby promoting breast cancer progression.
Spatially Resolved Tumor Ecosystems and Cell States in Gastric Adenocarcinoma Progression and Evolution
Authors: Haoran Ma, Supriya Srivastava, Shamaine Wei Ting Ho, Chang Xu, Benedict Shi Xiang Lian, Xuewen Ong, Su Ting Tay, Taotao Sheng, Huey Yew Jeffrey Lum, Siti Aishah Binte Abdul Ghani, Yunqiang Chu, Kie Kyon Huang, Yeek Teck Goh, Minghui Lee, Takeshi Hagihara, Clara Shi Ya Ng, Angie Lay Keng Tan, Yanrong Zhang, Zichen Ding, Feng Zhu, Michelle Shu Wen Ng, Craig Ryan Cecil Joseph, Hui Chen, Zhen Li, Joseph J. Zhao, Sun Young Rha, Ming Teh, Joe Yeong, Wei Peng Yong, Jimmy Bok-Yan So, Raghav Sundar, Patrick Tan
Journal: Cancer Discovery (2025)

Abstract Gastric cancer (GC) is a major cause of global cancer mortality with high levels of heterogeneity. To explore geospatial interactions in tumor ecosystems, we integrated 2,138 spatial transcriptomic regions-of-interest (ROIs) with 152,423 single-cell expression profiles across 226 GC samples from 121 patients. We observed pervasive expression-based intratumor heterogeneity, recapitulating tumor progression through spatially localized and functionally ordered subgroups associated with specific immune microenvironments, checkpoint profiles, and genetic drivers such as SOX9. Evolutionary phylogenetic analysis revealed two different evolutionary trajectories (branched evolution and internal diaspora evolution) associated with distinct molecular subtypes, clinical prognoses, and stromal neighborhoods including VWF+ ACKR1+ endothelial cells. Spatial analysis of tumor-stromal interfaces across multiple GCs highlighted new ecosystem states not attributable to mere tumor/stroma admixture, landmarked by increased GREM1 expression. Our results provide insights into how the cellular ecosystems of individual GCs are sculpted by tumor intrinsic and extrinsic selective pressures, culminating in individualized patient-specific cancer cartographies.
A novel prognostic risk model for patients with refractory/relapsed acute myeloid leukemia receiving venetoclax plus hypomethylating agents
Authors: Rabia Shahswar, Razif Gabdoulline, Katja Krueger, Martin Wichmann, Katharina S. Götze, Krischan Braitsch, Manja Meggendorfer, Laura Schmalbrock, Lars Bullinger, Franziska Modemann, Walter Fiedler, Juergen Krauter, Stephan Kaun, Susanne Rotermund, Andreas Voß, Yvonne Lisa Behrens, Anke Katharina Bergmann, Elisabeth Koller, Gernot Beutel, Felicitas Thol, Florian Heidel, Michael Heuser
Journal: Leukemia (2025)

Abstract Off-label hypomethylating agents and venetoclax (HMA/VEN) are often used for relapsed and refractory (R/R) AML patients. However, predictors of outcome are elusive. The objective of the current retrospective observational multicenter study of 240 adult patients (median age 68.6 years) with R/R AML was to establish a prognostic risk score. Overall response was documented in 106 (44%) patients. With a median follow-up of 31.5 months, 179 deaths were recorded. Median overall survival (mOS) was 7.9 months. In multivariate analysis of the subgroup with molecular information ( n = 174), risk factors for inferior survival included the presence of extramedullary disease, HMA pretreatment and mutations in NF1 , PTPN11 , FLT3 , and TP53 , whereas mutated SF3B1 was identified as favorable risk factor. These risk factors were subsequently applied to construct an HR-weighted risk model that allocated patients to one of three risk groups with significantly different survival outcomes: favorable ( n = 46; mOS 21.4 months), intermediate ( n = 75; mOS 7.5 months), and adverse ( n = 53; mOS 4.6 months; p &lt; 0.001). The model was validated in 189 AML patients treated with HMA/VEN in first line. This clinical-molecular, 3-tiered ven etoclax p rognostic r isk s core (VEN-PRS) for HMA/VEN treatment outcomes in R/R AML patients will support the selection of appropriate treatment options in this high-risk population.
Effectiveness of a Multifaceted Intervention (TEMP) for Prevention of Occupational Heat-Related Illness among Outdoor Workers in the Power Grid Industry: A Cluster Randomized Controlled Trial
Authors: Ranyi Ding, Yutong Wang, Yuelin Yu, Xianglong Meng, Quanquan Gong, Yuchuan Tang, Jinhao Wang, Xianlin Mu, Huiping Li, Huziwei Zhou, Shengfeng Wang, Ping Liu
Journal: Environmental Health Perspectives (2025)

Occupational heat-related illness (OHI) is a health threat to workers that can be fatal in severe cases. Effective and feasible measures are urgently needed to prevent OHI. We evaluated the effectiveness of a multifaceted intervention, TEMP, in reducing the OHI risk among outdoor workers in the power grid industry. A cluster randomized controlled trial was conducted with power grid outdoor workers in Southern China from 4 July 2022 to 28 August 2022. Work groups were randomly allocated (1:1) to the intervention or control groups. The multifaceted intervention TEMP comprised mobile application (app)-based education training (T), personal protective equipment [PPE (E)], OHI risk monitoring (M), and educational posters (P). Four follow-ups were conducted every 2 wk after the trial began. The primary outcome was the OHI incidence, and the secondary outcome was PPE usage. The app usage was considered as the compliance of intervention in the intervention group. The primary analysis used was intention-to-treat analysis. Multilevel analyses using random effects logistic regression models were performed to compare the odds of OHI between the two groups, adjusted for individual-level (education and work position) and work-related (including water intake when feeling thirsty, cooling measures, and poor sleep before work) covariates. Of 528 participants, 422 (79.92%) were males, and the mean±SD age was 36.36±8.18 y. The primary outcome, OHI incidence, was 1.80% in the intervention group and 4.82% in the control group at the end of the whole follow-up. OHI mainly occurred between 1100 and 1500 hours, with nausea, significantly increased heart rate, and oliguria being the top three reported OHI symptoms. Compared with the control group, the adjusted odds ratios between the intervention group and control group were 0.73 [95% confidence interval (CI): 0.30, 1.76] in the first follow-up wave, with 0.38 (95% CI: 0.15, 0.97), 0.29 (95% CI: 0.08, 1.05), and 0.39 (95% CI: 0.13, 1.19) in the following three follow-up waves, respectively. The intervention also significantly improved PPE usage in the intervention group. This multifaceted intervention reduced the OHI risk among outdoor workers in the power grid industry. However, further research is needed to design a more flexible intervention strategy and evaluate its effectiveness in a larger population. https://doi.org/10.1289/EHP14172.
Modeling GATA2 deficiency in mice: the R396Q mutation disrupts normal hematopoiesis
Authors: Trent Hall, Rashid Mehmood, Diana Sá da Bandeira, Anitria Cotton, Jonathon Klein, Shondra M. Pruett-Miller, Shai Izraeli, Wilson K. Clements, John D. Crispino
Journal: Leukemia (2025)

GATA2 deficiency is an autosomal dominant germline disorder of immune dysfunction and bone marrow failure with a high propensity for leukemic transformation. While sequencing studies have identified several secondary mutations thought to contribute to malignancy, the mechanisms of disease progression have been difficult to identify due to a lack of disease-specific experimental models. Here, we describe a murine model of one of the most common GATA2 mutations associated with leukemic progression in GATA2 deficiency, Gata2R396Q/+. While mutant mice exhibit mild defects in peripheral blood, they display significant hematopoietic abnormalities in the bone marrow, including a reduction in hematopoietic stem cell (HSC) function and intrinsic biases toward specific stem cell subsets that differ from previous models of GATA2 loss. Supporting this observation, single-cell RNA sequencing of hematopoietic progenitors revealed a loss of stemness, myeloid-bias, and indications of accelerated aging. Importantly, we show that Gata2R396Q/+ exerts effects early in hematopoietic development, as mutant mice generate fewer HSCs in the aorta gonad mesonephros, and fetal liver HSCs have reduced function. This reduced and altered pool of HSCs could be potential contributors to leukemic transformation in patients, and our model provides a useful tool to study the mechanisms of malignant transformation in GATA2 deficiency.
Orthogonal upconversion nanocarriers for combined photodynamic therapy and precisely triggered gene silencing in combating keloids
Authors: Wenchang Lv, Yiping Wu, Hongbo Chen
Journal: Journal of Controlled Release (2025)

Keloids are pathological scars characterized by excessive fibroblast proliferation, abnormal collagen deposition, and chronic inflammation, which often result in high recurrence rates and limited treatment success. Targeting BACH1 with gene therapy has shown promise in regulating fibroblast activity and reducing inflammation. However, effective delivery systems for targeted gene therapy in keloids remain a major challenge. Here, we develop a novel nanocarrier platform based on orthogonal upconversion nanoparticles (OUNCs) to achieve spatiotemporal silencing of BACH1 and combined photodynamic therapy (PDT). The OUNCs are composed of orthogonal upconversion nanoparticles (UCNPs), photosensitizer (Rose Bengal), ROS-sensitive diselenide bonds (SeSe), therapeutic siBACH1, and an active targeting moiety (hyaluronic acid) to specifically target keloid fibroblasts (KFs). We demonstrate that the OUNCs can effectively induce KFs apoptosis, inhibit KFs proliferation, and reduce M2 macrophages recruitment by modulating the Rap1/MEK/ERK signaling pathway. Our study represents a breakthrough in precision therapy for keloids, providing a promising platform that integrates siBACH1-based gene therapy with NIR light-triggered PDT.
Myocardial Fibroblast Activation After Acute Myocardial Infarction
Authors: Anna K Barton, Neil J Craig, Krithika Loganath, Shruti Joshi, Vasiliki Tsampasian, Menaka Mahendran, Joel Lenell, Evangelos Tzolos, Trisha Singh, Beth Whittington, Jennifer Nash, Michelle C Williams, Edwin J R van Beek, Mark G MacAskill, Bronwyn Berkeley, Stefan Vezaides, Mairi Brittan, Andrew H Baker, Stephanie Sellers, Alison Fletcher, Tim Clark, Clint Waight, Riemer H J A Slart, Daniel Berman, Damini Dey, Piotr Slomka, David E Newby, Marc R Dweck
Journal: Journal of the American College of Cardiology (2025)

Myocardial fibrosis is a key healing response after myocardial infarction driven by activated fibroblasts. Gallium-68-labeled fibroblast activation protein inhibitor ([68Ga]-FAPI) is a novel positron-emitting radiotracer that binds activated fibroblasts. The aim of this study was to investigate the intensity, distribution, and time-course of fibroblast activation after acute myocardial infarction. A total of 40 patients with acute myocardial infarction underwent hybrid [68Ga]FAPI-46 positron emission tomography and cardiac magnetic resonance and were compared with matched control subjects (n = 19) and those with chronic (>2 years) myocardial infarction (n = 20). Intensity of [68Ga]FAPI-46 uptake was quantified by maximum target-to-background ratio (TBRmax). Burdens of fibroblast activation and scar were assessed by percent myocardial involvement of [68Ga]FAPI-46 uptake and late gadolinium enhancement, respectively. Myocardial [68Ga]FAPI-46 uptake was observed in the acute infarct and peri-infarct regions that exceeded the extent of late gadolinium enhancement (burden 27.8% ± 12.4% vs 15.2% ± 10.6%; P < 0.001). One-third of patients also demonstrated right ventricular involvement. Myocardial [68Ga]FAPI-46 uptake was most intense at 1 and 2 weeks before declining at 4 and 12 weeks (TBRmax 4.0 ± 1.1, 3.7 ± 1.0, 3.1 ± 0.8, and 2.7 ± 0.7; P < 0.001). In comparison with control subjects, increased [68Ga]FAPI-46 uptake was observed in chronic (7 ± 6 years ago) infarcts at lower intensity than acute infarction (TBRmax 1.2 ± 0.1 vs 1.7 ± 0.5 vs 4.0 ± 1.1; P < 0.001). Baseline [68Ga]FAPI-46 burden correlated with lower left ventricular ejection fraction (r = -0.606), higher indexed left ventricular end-diastolic volume (r = 0.572), and higher scar burden (r = 0.871) at 1 year (P < 0.001 for all). Increased remote myocardial [68Ga]FAPI-46 uptake was associated with left ventricular dilatation and systolic dysfunction. Myocardial fibroblast activation peaks within a week of acute myocardial infarction and extends beyond the infarct region. It declines slowly with time, persists for years, and is associated with subsequent left ventricular remodeling. (PROFILE-MI-The FAPI Fibrosis Study; NCT05356923).