bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthesis and biological evaluation of echinomycin analogues as potential colon cancer agent
Authors: Kojima Keita , Konishi Hiroaki , Momosaki Kyoka , Komatani Yuya , Katsuyama Akira , Nakagawa Koji , Kanamitsu Kayoko , Yakushiji Fumika , Fujiya Mikihiro , Ichikawa Satoshi 
Published: April 2024

AbstractColorectal cancer is the third most commonly diagnosed cancer and the second leading cause of cancer-related death, thus a novel chemotherapeutic agent for colon cancer therapy is needed. In this study, analogues of echinomycin, a cyclic peptide natural product with potent toxicity to several human cancer cell lines, were synthesized, and their biological activities against human colon cancer cells were investigated. Analogue 3 as well as 1 inhibit HIF-1α-mediated transcription. Notably, transcriptome analysis indicated that the cell cycle and its regulation were involved in the effects on cells treated with 3. Analogue 3 exhibited superior in vivo efficacy to echinomycin without significant toxicity in mouse xenograft model. The low dose of 3 needed to be efficacious in vivo is also noteworthy and our data suggest that 3 is an attractive and potentially novel agent for the treatment of colon cancer.
Amyloid-β prediction machine learning model using source-based morphometry across neurocognitive disorders
Authors: Momota Yuki , Bun Shogyoku , Hirano Jinichi , Kamiya Kei , Ueda Ryo , Iwabuchi Yu , Takahata Keisuke , Yamamoto Yasuharu , Tezuka Toshiki , Kubota Masahito , Seki Morinobu , Shikimoto Ryo , Mimura Yu , Kishimoto Taishiro , Tabuchi Hajime , Jinzaki Masahiro , Ito Daisuke , Mimura Masaru 
Published: April 2024

AbstractPrevious studies have developed and explored magnetic resonance imaging (MRI)-based machine learning models for predicting Alzheimer’s disease (AD). However, limited research has focused on models incorporating diverse patient populations. This study aimed to build a clinically useful prediction model for amyloid-beta (Aβ) deposition using source-based morphometry, using a data-driven algorithm based on independent component analyses. Additionally, we assessed how the predictive accuracies varied with the feature combinations. Data from 118 participants clinically diagnosed with various conditions such as AD, mild cognitive impairment, frontotemporal lobar degeneration, corticobasal syndrome, progressive supranuclear palsy, and psychiatric disorders, as well as healthy controls were used for the development of the model. We used structural MR images, cognitive test results, and apolipoprotein E status for feature selection. Three-dimensional T1-weighted images were preprocessed into voxel-based gray matter images and then subjected to source-based morphometry. We used a support vector machine as a classifier. We applied SHapley Additive exPlanations, a game-theoretical approach, to ensure model accountability. The final model that was based on MR-images, cognitive test results, and apolipoprotein E status yielded 89.8% accuracy and a receiver operating characteristic curve of 0.888. The model based on MR-images alone showed 84.7% accuracy. Aβ-positivity was correctly detected in non-AD patients. One of the seven independent components derived from source-based morphometry was considered to represent an AD-related gray matter volume pattern and showed the strongest impact on the model output. Aβ-positivity across neurological and psychiatric disorders was predicted with moderate-to-high accuracy and was associated with a probable AD-related gray matter volume pattern. An MRI-based data-driven machine learning approach can be beneficial as a diagnostic aid.
A nomogram for predicting the risk of treatment failure of roxadustat in peritoneal dialysis with renal anemia
Authors: Fan Jiangqing , Lei Wenpu , Wang Lulu , Ge Weihong 
Published: April 2024

AbstractThe determinants of roxadustat treatment failure in renal anemia remain elusive. This study sought to develop a nomogram for predicting the risk of treatment failure of roxadustat in peritoneal dialysis (PD) with renal anemia. A retrospective cohort analysis from January 1, 2019, to January 31, 2023, included 204 PD patients with renal anemia, stratified by attainment group (Hb ≥ 110 g/L, n = 103) or non-attainment (Hb < 110 g/L, n = 101) within 1 year treatment. Univariate and multivariate Cox proportional hazards regressions were employed to ascertain predictive factors and construct the nomogram. Nomogram efficacy was evaluated via C-index, time-dependent ROC, calibration plots, and decision curve analysis, with internal validation via tenfold cross-validation and 1000 bootstrap resampling iterations. The study identified PD duration, serum transferrin, cardiovascular comorbidities, and stains as significant predictors. The nomogram demonstrated moderate discrimination at 6 months (AUC: 0.717) and enhanced predictive accuracy at 12 months (AUC: 0.741). The predicted and actual risk probabilities were concordant, with clinical net benefits observed at six-month (8 to 53%) and twelve-month (27 to 84%) risk thresholds. This nomogram is a valuable tool for effectively predicting non-attainment risk and facilitating personalized management of renal anemia in PD patients treated with roxadustat.
Optical property dataset of inorganic phosphor
Authors: Jang Seunghun , Na Gyoung S. , Choi Yunhee , Chang Hyunju 
Published: April 2024

AbstractDeveloping inorganic phosphor with desired properties for light-emitting diode application has traditionally relied on time-consuming and labor-intensive material development processes. Moreover, the results of material development research depend significantly on individual researchers’ intuition and experience. Thus, to improve the efficiency and reliability of materials discovery, machine learning has been widely applied to various materials science applications in recent years. However, the prediction capabilities of machine learning methods fundamentally depend on the quality of the training datasets. In this work, we constructed a high-quality and reliable dataset that contains experimentally validated inorganic phosphors and their optical properties, sourced from the literature on inorganic phosphors. Our dataset includes 3952 combinations of 21 dopant elements in 2238 host materials from 553 articles. The dataset provides material information, optical properties, measurement conditions for inorganic phosphors, and meta-information. Among the preliminary machine learning results, the essential properties of inorganic phosphors, such as maximum Photoluminescence (PL) emission wavelength and PL decay time, show overall satisfactory prediction performance with coefficient of determination ($$R^2$$

R
2

) scores of 0.7 or more. We also confirmed that the measurement conditions significantly improved prediction performance.
Educational simulator for mastoidectomy considering mechanical properties using 3D printing and its usability evaluation
Authors: Ock Junhyeok , Choi Yeonjoo , Lee Dong-Gyu , Chung Jong Woo , Kim Namkug 
Published: April 2024

AbstractComplex temporal bone anatomy complicates operations; thus, surgeons must engage in practice to mitigate risks, improving patient safety and outcomes. However, existing training methods often involve prohibitive costs and ethical problems. Therefore, we developed an educational mastoidectomy simulator, considering mechanical properties using 3D printing. The mastoidectomy simulator was modeled on computed tomography images of a patient undergoing a mastoidectomy. Infill was modeled for each anatomical part to provide a realistic drilling sensation. Bone and other anatomies appear in assorted colors to enhance the simulator’s educational utility. The mechanical properties of the simulator were evaluated by measuring the screw insertion torque for infill specimens and cadaveric temporal bones and investigating its usability with a five-point Likert-scale questionnaire completed by five otolaryngologists. The maximum insertion torque values of the sigmoid sinus, tegmen, and semicircular canal were 1.08 ± 0.62, 0.44 ± 0.42, and 1.54 ± 0.43 N mm, displaying similar-strength infill specimens of 40%, 30%, and 50%. Otolaryngologists evaluated the quality and usability at 4.25 ± 0.81 and 4.53 ± 0.62. The mastoidectomy simulator could provide realistic bone drilling feedback for educational mastoidectomy training while reinforcing skills and comprehension of anatomical structures.
Identification of ASF1A and HJURP by global H3–H4 histone chaperone analysis as a prognostic two-gene model in hepatocellular carcinoma
Authors: Liu Yongkang , Liu Shihui , Jing Rui , Li Congcong , Guo Yongqi , Cai Zhiye , Xi Pei , Dai Penggao , Jia Lintao , Zhu Hongli , Zhang Xiang 
Published: April 2024

AbstractHepatocellular carcinoma (HCC) is a malignancy with poor prognosis. Abnormal expression of H3–H4 histone chaperones has been identified in many cancers and holds promise as a biomarker for diagnosis and prognosis. However, systemic analysis of H3–H4 histone chaperones in HCC is still lacking. Here, we investigated the expression of 19 known H3–H4 histone chaperones in HCC. Integrated analysis of multiple public databases indicated that these chaperones are highly expressed in HCC tumor tissues, which was further verified by immunohistochemistry (IHC) staining in offline samples. Additionally, survival analysis suggested that HCC patients with upregulated H3–H4 histone chaperones have poor prognosis. Using LASSO and Cox regression, we constructed a two-gene model (ASF1A, HJURP) that accurately predicts prognosis in ICGC-LIRI and GEO HCC data, which was further validated in HCC tissue microarrays with follow-up information. GSEA revealed that HCCs in the high-risk group were associated with enhanced cell cycle progression and DNA replication. Intriguingly, HCCs in the high-risk group exhibited increased immune infiltration and sensitivity to immune checkpoint therapy (ICT). In summary, H3–H4 histone chaperones play a critical role in HCC progression, and the two-gene (ASF1A, HJURP) risk model is effective for predicting survival outcomes and sensitivity to immunotherapy for HCC patients.
Comparison of nine trauma scoring systems in prediction of inhospital outcomes of pediatric trauma patients: a multicenter study
Authors: Khavandegar Armin , Salamati Payman , Zafarghandi Mohammadreza , Rahimi-Movaghar Vafa , Sharif-Alhoseini Mahdi , Fakharian Esmaeil , Saeed-Banadaky Seyed Houssein , Hoseinpour Vahid , Sadeghian Farideh , Nasr Isfahani Mehdi , Rahmanian Vahid , Ghadiphasha Amir , Pourmasjedi Sobhan , Piri Seyed Mohammad , Mirzamohamadi Sara , Hassan Zadeh Tabatabaei Mahgol Sadat , Naghdi Khatereh , Baigi Vali 
Published: April 2024

AbstractHereby, we aimed to comprehensively compare different scoring systems for pediatric trauma and their ability to predict in-hospital mortality and intensive care unit (ICU) admission. The current registry-based multicenter study encompassed a comprehensive dataset of 6709 pediatric trauma patients aged ≤ 18 years from July 2016 to September 2023. To ascertain the predictive efficacy of the scoring systems, the area under the receiver operating characteristic curve (AUC) was calculated. A total of 720 individuals (10.7%) required admission to the ICU. The mortality rate was 1.1% (n = 72). The most predictive scoring system for in-hospital mortality was the adjusted trauma and injury severity score (aTRISS) (AUC = 0.982), followed by trauma and injury severity score (TRISS) (AUC = 0.980), new trauma and injury severity score (NTRISS) (AUC = 0.972), Glasgow coma scale (GCS) (AUC = 0.9546), revised trauma score (RTS) (AUC = 0.944), pre-hospital index (PHI) (AUC = 0.936), injury severity score (ISS) (AUC = 0.901), new injury severity score (NISS) (AUC = 0.900), and abbreviated injury scale (AIS) (AUC = 0.734). Given the predictive performance of the scoring systems for ICU admission, NTRISS had the highest predictive performance (AUC = 0.837), followed by aTRISS (AUC = 0.836), TRISS (AUC = 0.823), ISS (AUC = 0.807), NISS (AUC = 0.805), GCS (AUC = 0.735), RTS (AUC = 0.698), PHI (AUC = 0.662), and AIS (AUC = 0.651). In the present study, we concluded the superiority of the TRISS and its two derived counterparts, aTRISS and NTRISS, compared to other scoring systems, to efficiently discerning individuals who possess a heightened susceptibility to unfavorable consequences. The significance of these findings underscores the necessity of incorporating these metrics into the realm of clinical practice.
Differential cytokine expression in gastric tissues highlights helicobacter pylori’s role in gastritis
Authors: Yang Xing-Tang , Niu Pei-Qin , Li Xiao-Feng , Sun Ming-Ming , Wei Wei , Chen Yan-Qing , Zheng Jia-Yi 
Published: April 2024

AbstractHelicobacter pylori (H. pylori), known for causing gastric inflammation, gastritis and gastric cancer, prompted our study to investigate the differential expression of cytokines in gastric tissues, which is crucial for understanding H. pylori infection and its potential progression to gastric cancer. Focusing on Il-1β, IL-6, IL-8, IL-12, IL-18, and TNF-α, we analysed gene and protein levels to differentiate between H. pylori-infected and non-infected gastritis. We utilised real-time quantitative polymerase chain reaction (RT-qPCR) for gene quantification, immunohistochemical staining, and ELISA for protein measurement. Gastric samples from patients with gastritis were divided into three groups: (1) non-gastritis (N-group) group, (2) gastritis without H. pylori infection (G-group), and (3) gastritis with H. pylori infection (GH-group), each consisting of 8 samples. Our findings revealed a statistically significant variation in cytokine expression. Generally, cytokine levels were higher in gastritis, but in H. pylori-infected gastritis, IL-1β, IL-6, and IL-8 levels were lower compared to H. pylori-independent gastritis, while IL-12, IL-18, and TNF-α levels were higher. This distinct cytokine expression pattern in H. pylori-infected gastritis underscores a unique inflammatory response, providing deeper insights into its pathogenesis.
Clinical phenotype and genetic function analysis of a family with hypomyelinating leukodystrophy-7 caused by POLR3A mutation
Authors: Ruan Dan-dan , Ruan Xing-lin , Wang Ruo‑li , Lin Xin-fu , Zhang Yan-ping , Lin Bin , Li Shi-jie , Wu Min , Chen Qian , Zhang Jian-hui , Cheng Qiong , Zhang Yi-wu , Lin Fan , Luo Jie-wei , Zheng Zheng , Li Yun-fei 
Published: April 2024

AbstractHypomyelinating leukodystrophy (HLD) is a rare genetic heterogeneous disease that can affect myelin development in the central nervous system. This study aims to analyze the clinical phenotype and genetic function of a family with HLD-7 caused by POLR3A mutation. The proband (IV6) in this family mainly showed progressive cognitive decline, dentin dysplasia, and hypogonadotropic hypogonadism. Her three old brothers (IV1, IV2, and IV4) also had different degrees of ataxia, dystonia, or dysarthria besides the aforementioned manifestations. Their brain magnetic resonance imaging showed bilateral periventricular white matter atrophy, brain atrophy, and corpus callosum atrophy and thinning. The proband and her two living brothers (IV2 and IV4) were detected to carry a homozygous mutation of the POLR3A (NM_007055.4) gene c. 2300G > T (p.Cys767Phe), and her consanguineous married parents (III1 and III2) were p.Cys767Phe heterozygous carriers. In the constructed POLR3A wild-type and p.Cys767Phe mutant cells, it was seen that overexpression of wild-type POLR3A protein significantly enhanced Pol III transcription of 5S rRNA and tRNA Leu-CAA. However, although the mutant POLR3A protein overexpression was increased compared to the wild-type protein overexpression, it did not show the expected further enhancement of Pol III function. On the contrary, Pol III transcription function was frustrated (POLR3A, BC200, and tRNA Leu-CAA expression decreased), and MBP and 18S rRNA expressions were decreased. This study indicates that the POLR3A p.Cys767Phe variant caused increased expression of mutated POLR3A protein and abnormal expression of Pol III transcripts, and the mutant POLR3A protein function was abnormal.
Boxing behavior recognition based on artificial intelligence convolutional neural network with sports psychology assistant
Authors: Kong Yuanhui , Duan Zhiyuan 
Published: April 2024

AbstractThe purpose of this study is to deeply understand the psychological state of boxers before the competition, and explore an efficient boxing action classification and recognition model supported by artificial intelligence (AI) technology through these psychological characteristics. Firstly, this study systematically measures the key psychological dimensions of boxers, such as anxiety level, self-confidence, team identity, and opponent attitude, through psychological scale survey to obtain detailed psychological data. Then, based on these data, this study innovatively constructs a boxing action classification and recognition model based on BERT fusion 3D-ResNet, which not only comprehensively considers psychological information, but also carefully considers action characteristics to improve the classification accuracy of boxing actions. The performance evaluation shows that the model proposed in this study is significantly superior to the traditional model in terms of loss value, accuracy and F1 value, and the accuracy reaches 96.86%. Therefore, through the comprehensive application of psychology and deep learning, this study successfully constructs a boxing action classification and recognition model that can fully understand the psychological state of boxers, which provides strong support for the psychological training and action classification of boxers.
Hemispheric asymmetric response of tropical cyclones to CO2 emission reduction
Authors: Liu Chao , An Soon-Il , Zhao Jiuwei , Son Seok-Woo , Jin Fei-Fei , Zhan Ruifen 
Published: April 2024

AbstractTropical cyclones (TCs) are among the most devastating natural hazards for coastal regions, and their response to human activities has broad socio-economic relevance. So far, how TC responds to climate change mitigation remains unknown, complicating the design of adaptation policies. Using net-zero and negative carbon emission experiments, we reveal a robust hemisphere-asymmetric hysteretic TC response to CO2 reduction. During the decarbonization phase, the Northern Hemisphere TC frequency continues to decrease for several more decades, while the Southern Hemisphere oceans abruptly shifts to a stormier state, with the timescales depending on mitigation details. Such systematic changes are largely attributed to the planetary-scale reorganization of vertical wind shear and midlevel upward motion associated with the hysteretic southward migration of the Intertropical Convergence Zone, underpinned by the Atlantic Meridional Overturning Circulation and El Niño-like mean state changes. The hemispheric contrast in TC response suggests promising benefits for most of the world’s population from human action to mitigate greenhouse gas warming, but it may also exacerbate regional socioeconomic disparities, for example by putting more pressure on small open-ocean island states in the Southern Hemisphere to adapt to TC risks.
Post-therapy emergence of an NBN reversion mutation in a patient with pancreatic acinar cell carcinoma
Authors: Pelster Meredith S. , Silverman Ian M. , Schonhoft Joseph D. , Johnson Adrienne , Selenica Pier , Ulanet Danielle , Rimkunas Victoria , Reis-Filho Jorge S. 
Published: April 2024

AbstractPancreatic acinar cell carcinoma (PACC) is a rare form of pancreatic cancer that commonly harbors targetable alterations, including activating fusions in the MAPK pathway and loss-of-function (LOF) alterations in DNA damage response/homologous recombination DNA repair-related genes. Here, we describe a patient with PACC harboring both somatic biallelic LOF of NBN and an activating NTRK1 fusion. Upon disease progression following 13 months of treatment with folinic acid, fluorouracil, irinotecan, and oxaliplatin (FOLFIRINOX), genomic analysis of a metastatic liver biopsy revealed the emergence of a novel reversion mutation restoring the reading frame of NBN. To our knowledge, genomic reversion of NBN has not been previously reported as a resistance mechanism in any tumor type. The patient was treated with, but did not respond to, targeted treatment with a selective NTRK inhibitor. This case highlights the complex but highly actionable genomic landscape of PACC and underlines the value of genomic profiling of rare tumor types such as PACC.
Hybridized quantum dot, silica, and gold nanoparticles for targeted chemo-radiotherapy in colorectal cancer theranostics
Authors: Abrishami Amir , Bahrami Ahmad Reza , Nekooei Sirous , Sh. Saljooghi Amir , Matin Maryam M. 
Published: April 2024

AbstractMultimodal nanoparticles, utilizing quantum dots (QDs), mesoporous silica nanoparticles (MSNs), and gold nanoparticles (Au NPs), offer substantial potential as a smart and targeted drug delivery system for simultaneous cancer therapy and imaging. This method entails coating magnetic GZCIS/ZnS QDs with mesoporous silica, loading epirubicin into the pores, capping with Au NPs, PEGylation, and conjugating with epithelial cell adhesion molecule (EpCAM) aptamers to actively target colorectal cancer (CRC) cells. This study showcases the hybrid QD@MSN-EPI-Au-PEG-Apt nanocarriers (size ~65 nm) with comprehensive characterizations post-synthesis. In vitro studies demonstrate the selective cytotoxicity of these targeted nanocarriers towards HT-29 cells compared to CHO cells, leading to a significant reduction in HT-29 cell survival when combined with irradiation. Targeted delivery of nanocarriers in vivo is validated by enhanced anti-tumor effects with reduced side effects following chemo-radiotherapy, along with imaging in a CRC mouse model. This approach holds promise for improved CRC theranostics.
UFObow: A single-wavelength excitable Brainbow for simultaneous multicolor ex-vivo and in-vivo imaging of mammalian cells
Authors: Hu Jiahong , Yang Fangfang , Liu Chong , Wang Nengzhi , Xiao Yinghan , Zhai Yujie , Wang Xinru , Zhang Ren , Gao Lulu , Xu Mengli , Wang Jialu , Liu Zheng , Huang Songlin , Liu Wenfeng , Hu Yajing , Liu Feng , Guo Yuqi , Wang Liang , Yuan Jing , Zhang Zhihong , Chu Jun 
Published: April 2024

AbstractBrainbow is a genetic cell-labeling technique that allows random colorization of multiple cells and real-time visualization of cell fate within a tissue, providing valuable insights into understanding complex biological processes. However, fluorescent proteins (FPs) in Brainbow have distinct excitation spectra with peak difference greater than 35 nm, which requires sequential imaging under multiple excitations and thus leads to long acquisition times. In addition, they are not easily used together with other fluorophores due to severe spectral bleed-through. Here, we report the development of a single-wavelength excitable Brainbow, UFObow, incorporating three newly developed blue-excitable FPs. We have demonstrated that UFObow enables not only tracking the growth dynamics of tumor cells in vivo but also mapping spatial distribution of immune cells within a sub-cubic centimeter tissue, revealing cell heterogeneity. This provides a powerful means to explore complex biology in a simultaneous imaging manner at a single-cell resolution in organs or in vivo.