tbuckley/cabot-search huggingface dataset:
Synthesis and characterisation of a nucleotide based pro-drug formulated with a peptide into a nano-chemotherapy for colorectal cancer
Authors: Jordan J. Wilson, Lindsey Bennie, Olga Eguaogie, Ahmed Elkashif, Patrick F. Conlon, Lynn Jena, Emma McErlean, Niamh Buckley, Klaudia Englert, Nicholas J. Dunne, James H.R. Tucker, Joseph S. Vyle, Helen O. McCarthy
Journal: Journal of Controlled Release (2024)

Recent studies in colorectal cancer patients (CRC) have shown that increased resistance to thymidylate synthase (TS) inhibitors such as 5-fluorouracil (5-FU), reduce the efficacy of standard of care (SoC) treatment regimens. The nucleotide pool cleanser dUTPase is highly expressed in CRC and is an attractive target for potentiating anticancer activity of chemotherapy. The purpose of the current work was to investigate the activity of P1, P4-di(2′,5′-dideoxy-5′-selenouridinyl)-tetraphosphate (P4-SedU2), a selenium-modified symmetrically capped dinucleoside with prodrug capabilities that is specifically activated by dUTPase. Using mechanochemistry, P4-SedU2 and the corresponding selenothymidine analogue P4-SeT2 were prepared with a yield of 19% and 30% respectively. The phosphate functionality facilitated complexation with the amphipathic cell-penetrating peptide RALA to produce nanoparticles (NPs). These NPs were designed to deliver P4-SedU2 intracellularly and thereby maximise in vivo activity. The NPs demonstrated effective anti-cancer activity and selectivity in the HCT116 CRC cell line, a cell line that overexpresses dUTPase; compared to HT29 CRC cells and NCTC-929 fibroblast cells which have reduced levels of dUTPase expression. In vivo studies in BALB/c SCID mice revealed no significant toxicity with respect to weight or organ histology. Pharmacokinetic analysis of blood serum showed that RALA facilitates effective delivery and rapid internalisation into surrounding tissues with NPs eliciting lower plasma Cmax than the equivalent injection of free P4-SedU2, translating the in vitro findings. Tumour growth delay studies have demonstrated significant inhibition of growth dynamics with the tumour doubling time extended by >2weeks. These studies demonstrate the functionality and action of a new pro-drug nucleotide for CRC.
Bioactive peptide relieves glucocorticoid-induced osteoporosis by giant macrocyclic encapsulation
Authors: Yuna Shang, Qingrun Zhu, Jiaming Ding, Liang Zhao, Fan Zhang, Jiayi Lu, Yinyin Feng, Jiayu Wang, Zhixue Liu, Mingjie Kuang, Chunju Li
Journal: Journal of Controlled Release (2024)
Estimating crash risk and injury severity considering multiple traffic conflict and crash types: A bivariate extreme value approach
Authors: Md Mohasin Howlader, Fred Mannering, Md Mazharul Haque
Journal: Analytic Methods in Accident Research (2024)

Traffic conflicts are generally considered independent events in existing extreme value theory models to estimate the risk of total or single types of crashes. However, traffic events at a road entity are not necessarily independent interactions and can lead to multiple traffic conflicts with shared common unobserved factors. A comprehensive estimation of crash risks in a road entity needs to consider the correlation of potential traffic conflicts to avoid possible bias in prediction performance and the problem of undetected deficiencies. This study proposes a Bayesian non-stationary bivariate generalised extreme value modelling framework to estimate the severe and non-severe crash risks accounting for the correlation between right-turn and rear-end conflicts at signalised intersections. A deep neural network-based computer vision technique was applied to extract the traffic conflicts from 77 h of video recordings over two right-turn approaches at two signalised intersections in Cairns, Australia. Post encroachment time and modified time to collision were used to characterise right-turn and rear-end conflicts, respectively, while an expected post-collision velocity difference was combined with post encroachment time and modified time to collision for crash risk estimation by injury severity levels. Several covariates were used to address the time-varying heterogeneity of traffic conflict extremes and to estimate the differential crash risks at signal cycles. Results showed a significant correlation between right-turn and rear-end crashes at signal cycle levels, indicating the importance of accounting for the dependency among traffic conflict types. Overall, the bivariate models considering the correlation among traffic conflict types were found to understandably perform better than their univariate counterparts. This study provides a demonstration of a correlated crash risk modelling framework that addresses issues related to the suitable traffic conflict measures, time varying risks (non-stationarity), heterogeneity, and injury severity levels of different crash types.
Stepping forward: T-cell redirecting bispecific antibodies in cancer therapy
Authors: Xiaojing Qin, Wenjing Ning, Han Liu, Xue Liu, Wenxin Luo, Ningshao Xia
Journal: Acta Pharmaceutica Sinica B (2024)

T cell-redirecting bispecific antibodies are specifically designed to bind to tumor-associated antigens, thereby engaging with CD3 on the T cell receptor. This linkage between tumor cells and T cells actively triggers T cell activation and initiates targeted killing of the identified tumor cells. These antibodies have emerged as one of the most promising avenues within tumor immunotherapy. However, despite success in treating hematological malignancies, significant advancements in solid tumors have yet to be explored. In this review, we aim to address the critical challenges associated with T cell-redirecting bispecific antibodies and explore novel strategies to overcome these obstacles, with the ultimate goal of expanding the application of this therapy to include solid tumors.
Clinical perspective on topical vaccination strategies
Authors: Petya G. Popova, Sunny P. Chen, Suiyang Liao, Manish Sadarangani, Anna K. Blakney
Journal: Advanced Drug Delivery Reviews (2024)

Vaccination is one of the most successful measures in modern medicine to combat diseases, especially infectious diseases, and saves millions of lives every year. Vaccine design and development remains critical and involves many aspects, including the choice of platform, antigen, adjuvant, and route of administration. Topical vaccination, defined herein as the introduction of a vaccine to any of the three layers of the human skin, has attracted interest in recent years as an alternative vaccination approach to the conventional intramuscular administration because of its potential to be needle-free and induce a superior immune response against pathogens. In this review, we describe recent progress in developing topical vaccines, highlight progress in the development of delivery technologies for topical vaccines, discuss potential factors that might impact the topical vaccine efficacy, and provide an overview of the current clinical landscape of topical vaccines.
A novel in‐frame deletion in KIF5C gene causes infantile onset epilepsy and psychomotor retardation
Authors: Santasree Banerjee, Qiang Zhao, Bo Wang, Jiale Qin, Xin Yuan, Ziwei Lou, Weizeng Zheng, Huanguo Li, Xiaojun Wang, Xiawei Cheng, Yu Zhu, Fan Lin, Fan Yang, Junyu Xu, Anjana Munshi, Parimal Das, Yuanfeng Zhou, Kausik Mandal, Yi Wang, Muhammad Ayub, Nobutaka Hirokawa, Yongmei Xi, Guangfu Chen, Chen Li
Journal: MedComm (2024)

Abstract Motor proteins, encoded by Kinesin superfamily ( KIF ) genes, are critical for brain development and plasticity. Increasing studies reported KIF ’s roles in neurodevelopmental disorders. Here, a 6 years and 3 months‐old Chinese boy with markedly symptomatic epilepsy, intellectual disability, brain atrophy, and psychomotor retardation was investigated. His parents and younger sister were phenotypically normal and had no disease‐related family history. Whole exome sequencing identified a novel heterozygous in‐frame deletion (c.265_267delTCA) in exon 3 of the KIF5C in the proband, resulting in the removal of evolutionarily highly conserved p.Ser90, located in its ATP‐binding domain. Sanger sequencing excluded the proband's parents and family members from harboring this variant. The activity of ATP hydrolysis in vitro was significantly reduced as predicted. Immunofluorescence studies showed wild‐type KIF5C was widely distributed throughout the cytoplasm, while mutant KIF5C was colocalized with microtubules. The live‐cell imaging of the cargo‐trafficking assay revealed that mutant KIF5C lost the peroxisome‐transporting ability. Drosophila models also confirmed p.Ser90del's essential role in nervous system development. This study emphasized the importance of the KIF5C gene in intracellular cargo‐transport as well as germline variants that lead to neurodevelopmental disorders and might enable clinicians for timely and accurate diagnosis and disease management in the future.
cGAS–STING, an important signaling pathway in diseases and their therapy
Authors: Qijie Li, Ping Wu, Qiujing Du, Ullah Hanif, Hongbo Hu, Ka Li
Journal: MedComm (2024)

Abstract Since cyclic guanosine monophosphate‐adenosine monophosphate synthase (cGAS)–stimulator of interferon genes (STING) signaling pathway was discovered in 2013, great progress has been made to elucidate the origin, function, and regulating mechanism of cGAS–STING signaling pathway in the past decade. Meanwhile, the triggering and transduction mechanisms have been continuously illuminated. cGAS–STING plays a key role in human diseases, particularly DNA‐triggered inflammatory diseases, making it a potentially effective therapeutic target for inflammation‐related diseases. Here, we aim to summarize the ancient origin of the cGAS–STING defense mechanism, as well as the triggers, transduction, and regulating mechanisms of the cGAS–STING. We will also focus on the important roles of cGAS–STING signal under pathological conditions, such as infections, cancers, autoimmune diseases, neurological diseases, and visceral inflammations, and review the progress in drug development targeting cGAS–STING signaling pathway. The main directions and potential obstacles in the regulating mechanism research and therapeutic drug development of the cGAS–STING signaling pathway for inflammatory diseases and cancers will be discussed. These research advancements expand our understanding of cGAS–STING, provide a theoretical basis for further exploration of the roles of cGAS–STING in diseases, and open up new strategies for targeting cGAS–STING as a promising therapeutic intervention in multiple diseases.
Generation and utilization of endostatin‐sensitive cell lines for assessing the biological activity of endostatin
Authors: Xi Qin, Yifang An, Xiang Li, Fang Huang, Yong Zhou, Dening Pei, Hua Bi, Xinchang Shi, Wenhong Fan, Youxue Ding, Shuang Li, Shanhu Li, Junzhi Wang
Journal: MedComm (2024)

Abstract Recombinant proteins are gaining increasing popularity for treating human diseases. The clinical effectiveness of recombinant proteins is directly related to their biological activity, which is an important indicator in drug development and quality control. However, certain recombinant proteins have unclear or complex signal pathways, making detecting their activity in vitro difficult. For instance, recombinant human endostatin (endostatin), a new antitumor drug developed in China, lacks a sensitive and stable assay for its biological activity since being market approval. To address this issue, we performed a genome‐wide screening of immortalized human umbilical vein endothelial cells (HUVECs) using a CRISPR/Cas9 knockout library containing 20,000 targeted genes. We identified two potential endostatin‐resistant genes, NEPSPP and UTS2, and successfully constructed a highly sensitive cell line, HUVEC‐UTS2‐3#, by knocking down the UTS2 gene. Based on the optimized parameters of HUVEC‐UTS2‐3# cells, we established a new method for detecting the biological activity of endostatin. The method was validated, and it produced results consistent with primary HUVEC cells but with higher sensitivity and more stable data. The use of gene‐editing technology provides a novel solution for detecting the biological activity of recombinant proteins that other methods cannot detect.
Multidrug-resistant tuberculosis
Authors: Keertan Dheda, Fuad Mirzayev, Daniela Maria Cirillo, Zarir Udwadia, Kelly E. Dooley, Kwok-Chiu Chang, Shaheed Vally Omar, Anja Reuter, Tahlia Perumal, C. Robert Horsburgh, Megan Murray, Christoph Lange
Journal: Nature Reviews Disease Primers (2024)
Design and development of novel self-assembled catechol-modified bile acid conjugates as pH-responsive apical sodium-dependent bile acid transporter targeting nanoparticles
Authors: Dong-Nyeong Lee, Seong-Bin Yang, Seho Kweon, Jun-Hyuck Lee, Kyeong-Ju Lee, Yeonsu Ryu, Dong Wook Shin, Young Jun Kim, Yong-Kyu Lee, Jooho Park
Journal: Biomaterials (2024)
Diabetic foot ulcers segmentation challenge report: Benchmark and analysis
Authors: Moi Hoon Yap, Bill Cassidy, Michal Byra, Ting-yu Liao, Huahui Yi, Adrian Galdran, Yung-Han Chen, Raphael Brüngel, Sven Koitka, Christoph M. Friedrich, Yu-wen Lo, Ching-hui Yang, Kang Li, Qicheng Lao, Miguel A. González Ballester, Gustavo Carneiro, Yi-Jen Ju, Juinn-Dar Huang, Joseph M. Pappachan, Neil D. Reeves, Vishnu Chandrabalan, Darren Dancey, Connah Kendrick
Journal: Medical Image Analysis (2024)

Monitoring the healing progress of diabetic foot ulcers is a challenging process. Accurate segmentation of foot ulcers can help podiatrists to quantitatively measure the size of wound regions to assist prediction of healing status. The main challenge in this field is the lack of publicly available manual delineation, which can be time consuming and laborious. Recently, methods based on deep learning have shown excellent results in automatic segmentation of medical images, however, they require large-scale datasets for training, and there is limited consensus on which methods perform the best. The 2022 Diabetic Foot Ulcers segmentation challenge was held in conjunction with the 2022 International Conference on Medical Image Computing and Computer Assisted Intervention, which sought to address these issues and stimulate progress in this research domain. A training set of 2000 images exhibiting diabetic foot ulcers was released with corresponding segmentation ground truth masks. Of the 72 (approved) requests from 47 countries, 26 teams used this data to develop fully automated systems to predict the true segmentation masks on a test set of 2000 images, with the corresponding ground truth segmentation masks kept private. Predictions from participating teams were scored and ranked according to their average Dice similarity coefficient of the ground truth masks and prediction masks. The winning team achieved a Dice of 0.7287 for diabetic foot ulcer segmentation. This challenge has now entered a live leaderboard stage where it serves as a challenging benchmark for diabetic foot ulcer segmentation.
Corrigendum to “Effectiveness and safety of tuberculosis preventive treatment for contacts of patients with multidrug-resistant tuberculosis: a systematic review and meta-analysis” [Clin Microbiol Infect 30 (2024) 189–196]
Authors: G. Zhou, S. Luo, J. He, N. Chen, Y. Zhang, S. Cai, X. Guo, H. Chen, C. Song
Journal: Clinical Microbiology and Infection (2024)
Treatment response and clinical event-free survival in autoimmune hepatitis: A Canadian multicentre cohort study
Authors: Christina G. Plagiannakos, Gideon M. Hirschfield, Ellina Lytvyak, Surain B. Roberts, Marwa Ismail, Aliya F. Gulamhusein, Nazia Selzner, Karim M. Qumosani, Lawrence Worobetz, Julian Hercun, Catherine Vincent, Jennifer A. Flemming, Mark G. Swain, Angela Cheung, Tianyan Chen, Dusanka Grbic, Kevork Peltekain, Andrew L. Mason, Aldo J. Montano-Loza, Bettina E. Hansen
Journal: Journal of Hepatology (2024)

Treatment outcomes for people living with autoimmune hepatitis (AIH) are limited by a lack of specific therapies, as well as limited well-validated prognostic tools and clinical trial endpoints. We sought to identify predictors of outcome for people living with AIH.
Developing and validating clinical prediction models in hepatology – An overview for clinicians
Authors: Rickard Strandberg, Peter Jepsen, Hannes Hagström
Journal: Journal of Hepatology (2024)

Prediction models are everywhere in clinical medicine. We use them to assign a diagnosis or a prognosis, and there is a continuous effort to develop better prediction models. It is important to understand the fundamentals of prediction modeling, and here we describe nine steps to develop and validate a clinical prediction model with the intention of implementing it in clinical practice: Determine if there is a need for a new prediction model; define the purpose and intended use for the model; assess the quality and quantity of the data you wish to develop the model on; develop the model using sound statistical methods; generate risk predictions on the probability scale (0-100%); evaluate the performance of the model in terms of discrimination, calibration, and clinical utility; validate the model using bootstrapping to correct for the apparent optimism in performance; validate the model on external datasets to assess the generalizability and transportability of the model; and finally publish the model so that it can be implemented or validated by others.
Renal infarction secondary to Aspergillus spp. embolism following COVID-19
Authors: Precil Diego Miranda de Menezes Neves, Sara Mohrbacher, Igor Lobato Vasques, Lívia Barreira Cavalcante, Victor Augusto Hamamoto Sato, Érico de Souza Oliveira, Leonardo Victor Barbosa Pereira, Alessandra Martins Bales, Marcella Martins Frediani, Pedro Renato Chocair, Américo Lourenço Cuvello-Neto
Journal: The Lancet Infectious Diseases (2024)
Deep Learning to Estimate Cardiovascular Risk From Chest Radiographs
Authors: Jakob Weiss, Vineet K. Raghu, Kaavya Paruchuri, Aniket Zinzuwadia, Pradeep Natarajan, Hugo J.W.L. Aerts, Michael T. Lu
Journal: Annals of Internal Medicine (2024)

Guidelines for primary prevention of atherosclerotic cardiovascular disease (ASCVD) recommend a risk calculator (ASCVD risk score) to estimate 10-year risk for major adverse cardiovascular events (MACE). Because the necessary inputs are often missing, complementary approaches for opportunistic risk assessment are desirable.
Evaluation of Strategies for Transitioning to Annual SARS-CoV-2 Vaccination Campaigns in the United States
Authors: Chad R. Wells, Abhishek Pandey, Seyed M. Moghadas, Meagan C. Fitzpatrick, Burton H. Singer, Alison P. Galvani
Journal: Annals of Internal Medicine (2024)

The U.S. Food and Drug Administration has proposed administering annual SARS-CoV-2 vaccines. To evaluate the effectiveness of an annual SARS-CoV-2 vaccination campaign, quantify the health and economic benefits of a second dose provided to children younger than 2 years and adults aged 50 years or older, and optimize the timing of a second dose. An age-structured dynamic transmission model. United States. A synthetic population reflecting demographics and contact patterns in the United States. Vaccination against SARS-CoV-2 with age-specific uptake similar to that of influenza vaccination. Incidence, hospitalizations, deaths, and direct health care cost. The optimal timing between the first and second dose delivered to children younger than 2 years and adults aged 50 years or older in an annual vaccination campaign was estimated to be 5 months. In direct comparison with a single-dose campaign, a second booster dose results in 123 869 fewer hospitalizations (95% uncertainty interval [UI], 121 994 to 125 742 fewer hospitalizations) and 5524 fewer deaths (95% UI, 5434 to 5613 fewer deaths), averting $3.63 billion (95% UI, $3.57 billion to $3.69 billion) in costs over a single year. Population immunity is subject to degrees of immune evasion for emerging SARS-CoV-2 variants. The model was implemented in the absence of nonpharmaceutical interventions and preexisting vaccine-acquired immunity. The direct health care costs of SARS-CoV-2, particularly among adults aged 50 years or older, would be substantially reduced by administering a second dose 5 months after the initial dose. Natural Sciences and Engineering Research Council of Canada, Notsew Orm Sands Foundation, National Institutes of Health, Centers for Disease Control and Prevention, and National Science Foundation.
Dapagliflozin and Days of Full Health Lost in the DAPA-HF Trial
Authors: Toru Kondo, Ulrik M. Mogensen, Atefeh Talebi, Samvel B. Gasparyan, Ross T. Campbell, Kieran F. Docherty, Rudolf A. de Boer, Silvio E. Inzucchi, Lars Køber, Mikhail N. Kosiborod, Felipe A. Martinez, Marc S. Sabatine, Olof Bengtsson, Mikaela Sjöstrand, Muthiah Vaduganathan, Scott D. Solomon, Pardeep S. Jhund, John J.V. McMurray
Journal: Journal of the American College of Cardiology (2024)

Conventional time-to-first-event analyses cannot incorporate recurrent hospitalizations and patient well-being in a single outcome. To overcome this limitation, we tested an integrated measure that includes days lost from death and hospitalization, and additional days of full health lost through diminished well-being. The effect of dapagliflozin on this integrated measure was assessed in the DAPA-HF trial, which examined the efficacy of dapagliflozin, compared with placebo, in patients with NYHA class II-IV HF and a LVEF ≤40%. Over 360 days, patients in the dapagliflozin group (n=2,127) lost 10.6±1.0 [mean±SE] (2.9%) of potential follow-up days through cardiovascular death and HF hospitalization, compared with 14.4±1.0 days (4.0%) in the placebo group (n=2,108), and this component of all measures of days lost accounted for the greatest between-treatment difference [-3.8 (95%CI -6.6 to -1.0) days]. Patients receiving dapagliflozin also had fewer days lost to death and hospitalization from all causes, versus placebo [15.5±1.1 days (4.3%) vs. 20.3±1.1 days (5.6%)]. When additional days of full health lost (i.e., adjusted for KCCQ-OSS) were added, total days lost were 110.6±1.6 (30.7%) with dapagliflozin vs.116.9±1.6 days (32.5%) with placebo]. The difference in all measures between the two groups increased over time; i.e., days lost by death and hospitalization -0.9 days (-0.7%) at 120 days, -2.3 days (-1.0%) at 240 days, and -4.8 days (-1.3%) at 360 days. Dapagliflozin reduced the total days of potential full health lost due to death, hospitalizations, and impaired well-being, and this benefit increased over time during the first year.