bluuebunny/crossref_metadata_2025_split huggingface dataset:
TCP1 expression alters the ferroptosis sensitivity of diffuse large B-cell lymphoma subtypes by stabilising ACSL4 and influences patient prognosis
Authors: Zhang Shuxia , Wang Jin , Huang Guanxiang , Xiao Xueting , Xu Shujuan , Weng Ping , Wang Yiting , Tian Huiyun , Huang Huifang , Chen Yuanzhong 
Published: August 2024

AbstractDiffuse large B-cell lymphoma (DLBCL), an invasive lymphoma with substantial heterogeneity, can be mainly categorised into germinal centre B-cell-like (GCB) and non-GCB subtypes. DLBCL cells are highly susceptible to ferroptosis, which offers an effective avenue for treating recurrent and refractory DLBCL. Moreover, various heat shock proteins are involved in regulating the sensitivity of tumour cells to ferroptosis. Among these proteins, tailless complex polypeptide 1 (TCP1), a subunit of chaperonin-containing T-complex protein-1 (CCT), plays a role in tumour proliferation and survival. Therefore, we explored the role of TCP1 in different DLBCL subtypes, the sensitivity of GCB and non-GCB subtypes to the ferroptosis inducer RAS-selective lethal small molecule 3 (RSL3), and the underlying molecular mechanism. In GCB cells, TCP1 promoted RSL3-induced ferroptosis. Notably, TCP1 could bind with acyl-CoA synthetase long-chain family member 4 (ACSL4), a key enzyme regulating lipid composition and facilitating ferroptosis, to reduce its ubiquitination and degradation. This interaction activated the ACSL4/LPCAT3 signalling pathway and promoted ferroptosis in the GCB subtype. However, in the non-GCB subtype, TCP1 did not act as a positive regulator but served as a predictor of an unfavourable prognosis in patients with non-GCB. In conclusion, our results suggest that in DLBCL, high TCP1 expression enhances the sensitivity of GCB tumour cells to ferroptosis and serves as a marker of poor prognosis in patients with non-GCB DLBCL.
UK Reproducibility Network open and transparent research practices survey dataset
Authors: Hughes-Noehrer Lukas , Aubert Bonn Noémie , De Maria Marcello , Evans Thomas Rhys , Farran Emily K. , Fortunato Laura , Henderson Emma L. , Jacobs Neil , Munafò Marcus R. , Stewart Suzanne L. K. , Stewart Andrew J. 
Published: August 2024

AbstractOpenness and transparency in the research process are a prerequisite to the production of high quality research outputs. Efforts to maximise these features have substantially accelerated in recent years, placing open and transparent research practices at the forefront of funding and related priorities, and encouraging investment in resources and infrastructure to enable such practices. Despite these efforts, there has been no systematic documentation of current practices, infrastructure, or training and resources that support open and transparent research in the UK. To address this gap, we developed and conducted the Open and Transparent Research Practices survey, a large-scale audit study completed by research-active staff in UK research institutions to better understand existing practices, needs, support, and barriers faced when implementing open and transparent research. The data presented here capture responses from over 2,500 research-active staff based at 15 institutions affiliated with the UK Reproducibility Network. The data provide a snapshot of open research practices that can be used to identify barriers, training needs, and areas that require greater investments.
Enhancing colorectal cancer histology diagnosis using modified deep neural networks optimizer
Authors: Elshamy Reham , Abu-Elnasr Osama , Elhoseny Mohamed , Elmougy Samir 
Published: August 2024

AbstractOptimizers are the bottleneck of the training process of any Convolutionolution neural networks (CNN) model. One of the critical steps when work on CNN model is choosing the optimal optimizer to solve a specific problem. Recent challenge in nowadays researches is building new versions of traditional CNN optimizers that can work more efficient than the traditional optimizers. Therefore, this work proposes a novel enhanced version of Adagrad optimizer called SAdagrad that avoids the drawbacks of Adagrad optimizer in dealing with tuning the learning rate value for each step of the training process. In order to evaluate SAdagrad, this paper builds a CNN model that combines a fine- tuning technique and a weight decay technique together. It trains the proposed CNN model on Kather colorectal cancer histology dataset which is one of the most challenging datasets in recent researches of Diagnose of Colorectal Cancer (CRC). In fact, recently, there have been plenty of deep learning models achieving successful results with regard to CRC classification experiments. However, the enhancement of these models remains challenging. To train our proposed model, a learning transfer process, which is adopted from a pre-complicated defined model is applied to the proposed model and combined it with a regularization technique that helps in avoiding overfitting. The experimental results show that SAdagrad reaches a remarkable accuracy (98%), when compared with Adaptive momentum optimizer (Adam) and Adagrad optimizer. The experiments also reveal that the proposed model has a more stable training and testing processes, can reduce the overfitting problem in multiple epochs and can achieve a higher accuracy compared with previous researches on Diagnosis CRC using the same Kather colorectal cancer histology dataset.
Estimating the strength of bi-axially loaded track and channel cold formed composite column using different AI-based symbolic regression techniques
Authors: Ebid Ahmed M. , El-Aghoury Mohamed A. , Onyelowe Kennedy C. , Ors Dina M. 
Published: August 2024

AbstractSteel construction is increasingly using thin-walled profiles to achieve lighter, more cost-effective structures. However, analyzing the behavior of these elements becomes very complex due to the combined effects of local buckling in the thin walls and overall global buckling of the entire column. These factors make traditional analytical methods difficult to apply. Hence, in this research work, the strength of bi-axially loaded track and channel cold formed composite column has been estimated by applying three AI-based symbolic regression techniques namely (GP), (EPR) and (GMDH-NN). These techniques were selected because their output models are closed form equations that could be manually used. The methodology began with collecting a 90 records database from previous researches and conducting statistical, correlation and sensitivity analysis, and then the database was used to train and validate the three models. All the models used local and global slenderness ratios (λ, λc, λt) and relative eccentricities (ex/D, ey/B) as inputs and (F/Fy) as output. The performances of the developed models were compared with the predicted capacities from two design codes (AISI and EC3). The results showed that both design codes have prediction error of 33% while the three developed models showed better performance with error percent of 6%, and the (EPR) model is the simplest one. Also, both correlation and sensitivity analysis showed that the global slenderness ratio (λ) has the main influence on the strength, then the relative eccentricities (ex/D, ey/B) and finally the local slenderness ratios (λc, λt).
Infection Inspection: using the power of citizen science for image-based prediction of antibiotic resistance in Escherichia coli treated with ciprofloxacin
Authors: Farrar Alison , Feehily Conor , Turner Piers , Zagajewski Alexander , Chatzimichail Stelios , Crook Derrick , Andersson Monique , Oakley Sarah , Barrett Lucinda , El Sayyed Hafez , Fowler Philip W. , Nellåker Christoffer , Kapanidis Achillefs N. , Stoesser Nicole 
Published: August 2024

AbstractAntibiotic resistance is an urgent global health challenge, necessitating rapid diagnostic tools to combat its threat. This study uses citizen science and image feature analysis to profile the cellular features associated with antibiotic resistance in Escherichia coli. Between February and April 2023, we conducted the Infection Inspection project, in which 5273 volunteers made 1,045,199 classifications of single-cell images from five E. coli strains, labelling them as antibiotic-sensitive or antibiotic-resistant based on their response to the antibiotic ciprofloxacin. User accuracy in image classification reached 66.8 ± 0.1%, lower than our deep learning model's performance at 75.3 ± 0.4%, but both users and the model were more accurate when classifying cells treated at a concentration greater than the strain’s own minimum inhibitory concentration. We used the users’ classifications to elucidate which visual features influence classification decisions, most importantly the degree of DNA compaction and heterogeneity. We paired our classification data with an image feature analysis which showed that most of the incorrect classifications happened when cellular features varied from the expected response. This understanding informs ongoing efforts to enhance the robustness of our diagnostic methodology. Infection Inspection is another demonstration of the potential for public participation in research, specifically increasing public awareness of antibiotic resistance.
Selective nanosecond laser removal of retinal pigment epithelium for cell therapy
Authors: Nguyen Van Phuc , Karoukis Athanasios J. , Hu Justin , Wei Zhuying , Yang Dongshan , Fahim Abigail T. , Wang Xueding , Paulus Yannis M. 
Published: August 2024

AbstractRetinal pigment epithelial (RPE) cells play a crucial role in the health of the retina, and their dysfunction is associated with various ocular diseases. The transplantation of RPE cells has been proposed as a potential treatment for numerous degenerative diseases, including geographic atrophy from macular degeneration. However, current models to induce RPE damage in animal models prior to transplantation involve mechanical scraping, chemical administration, or laser photocoagulation techniques, which can damage the overlying neurosensory retina. This study aims to investigate the feasibility and efficacy of nanosecond duration laser treatment to safely remove large areas of RPE cells without causing damage to the adjacent tissue or affecting the retinal architecture. Twelve pigmented rabbits were treated with a nanosecond laser on each eye at a laser energy ranging from 200 to 800 nJ with a treated area of 5 × 5 mm2. Human induced pluripotent stem cells-differentiated to RPE (hiPSC-RPE) cells labeled with indocyanine green (ICG), an FDA approved dye, were transplanted subretinally into the damaged RPE areas at day 14 post-laser treatment. The RPE atrophy and hiPSC-RPE cell survival was evaluated and monitored over a period of 14 days using color photography, fluorescein angiography (FA), photoacoustic microscopy (PAM), and optical coherence tomography (OCT) imaging. All treated eyes demonstrated focal RPE loss with a success rate of 100%. The injured RPE layers and the transplanted hiPSC-RPE cells were visualized in three dimensions using PAM and OCT. By performing PAM at an optical wavelength of 700 nm, the location of hiPSC-RPE cells were identified and distinguished from the surrounding RPE cells, and the induced PA signal increased up to 18 times. Immunohistochemistry results confirmed the grafted hiPSC-RPE replaced regions of RPE damage. This novel technique has the potential to serve as an animal model of RPE degeneration, to improve models of RPE transplantation, and may help accelerate translation of this therapeutic strategy for clinical use.
Derived neutrophil-to-lymphocyte ratio has the potential to predict safety and outcomes of durvalumab after chemoradiation in non-small cell lung cancer
Authors: Sugimoto Akira , Kaneda Hiroyasu , Yoshimoto Naoki , Nagata Kenji , Fujii Tatsuo , Michimoto Koichi , Ueno Shunsuke , Kamimori Takao , Ishii Yoshie , Sakagami Mai , Inokuchi Haruo , Shibuya Keiko , Mizutani Megumi , Nagamine Hiroaki , Nakahama Kenji , Matsumoto Yoshiya , Tani Yoko , Sawa Kenji , Kawaguchi Tomoya 
Published: August 2024

AbstractThe usefulness of the derived neutrophil-to-lymphocyte ratio (dNLR) and its dynamics before/after durvalumab consolidation therapy to predict safety or efficacy remains unclear. We retrospectively reviewed patients with locally advanced non-small cell lung cancer treated with durvalumab consolidation therapy after chemoradiotherapy (D group) or chemoradiotherapy alone (non-D group) at multiple institutions. We investigated the association between dNLR, or its dynamics, and pneumonitis, checkpoint inhibitor-related pneumonitis (CIP), irAEs, and efficacy. Ninety-eight and fifty-six patients were enrolled in the D and non-D groups, respectively. The dNLR at baseline was significantly lower in patients who experienced irAEs or CIP than in those who did not. The low dNLR group, 28 days following durvalumab consolidation therapy (dNLR28 ≤ 3), demonstrated longer progression-free survival (PFS) and overall survival (OS) than the high dNLR group (dNLR28 > 3) (PFS, hazard ratio [HR] 0.44, 95% confidence interval [CI] 0.22–0.88, p = 0.020; OS, HR 0.39, 95% CI 0.16–0.94, p = 0.037). Among patients with high dNLR at baseline (dNLR > 3), the dNLR28 ≤ 3 group showed longer PFS than the dNLR28 > 3 group (p = 0.010). The dNLR is a predictive factor for irAEs and CIP in patients receiving durvalumab consolidation therapy. The dNLR at 28 days after durvalumab consolidation therapy and its dynamics predict favorable outcomes.
Novel druggable space in human KRAS G13D discovered using structural bioinformatics and a P-loop targeting monoclonal antibody
Authors: Jungholm Oscar , Trkulja Carolina , Moche Martin , Srinivasa Sreesha P. , Christakopoulou Maria-Nefeli , Davidson Max , Reymer Anna , Jardemark Kent , Fogaça Rafaela Lenza , Ashok Anaswara , Jeffries Gavin , Ampah-Korsah Henry , Strandback Emilia , Andréll Juni , Nyman Tomas , Nouairia Ghada , Orwar Owe 
Published: August 2024

AbstractKRAS belongs to a family of small GTPases that act as binary switches upstream of several signalling cascades, controlling proliferation and survival of cells. Mutations in KRAS drive oncogenesis, especially in pancreatic, lung, and colorectal cancers (CRC). Although historic attempts at targeting mutant KRAS with small molecule inhibitors have proven challenging, there are recent successes with the G12C, and G12D mutations. However, clinically important RAS mutations such as G12V, G13D, Q61L, and A146T, remain elusive drug targets, and insights to their structural landscape is of critical importance to develop novel, and effective therapeutic concepts. We present a fully open, P-loop exposing conformer of KRAS G13D by X-ray crystallography at 1.4–2.4 Å resolution in Mg2+-free phosphate and malonate buffers. The G13D conformer has the switch-I region displaced in an upright position leaving the catalytic core fully exposed. To prove that this state is druggable, we developed a P-loop-targeting monoclonal antibody (mAb). The mAb displayed high-affinity binding to G13D and was shown using high resolution fluorescence microscopy to be spontaneously taken up by G13D-mutated HCT 116 cells (human CRC derived) by macropinocytosis. The mAb inhibited KRAS signalling in phosphoproteomic and genomic studies. Taken together, the data propose novel druggable space of G13D that is reachable in the cellular context. It is our hope that these findings will stimulate attempts to drug this fully open state G13D conformer using mAbs or other modalities.
Hedgehog components are overexpressed in a series of liver cancer cases
Authors: Sales Caroline Brandi Schlaepfer , Dias Rosane Borges , de Faro Valverde Ludmila , Bomfim Larissa M. , Silva Lais Almeida , de Carvalho Nanashara C. , Bastos Jorge Luiz Andrade , Tilli Tatiana Martins , Rocha Gisele Vieira , Soares Milena Botelho Pereira , de Freitas Luiz Antonio Rodrigues , Gurgel Rocha Clarissa A. , Bezerra Daniel P. 
Published: August 2024

AbstractLiver cancers, including hepatocellular carcinoma (HCC), are the sixth most common cancer and the third leading cause of cancer-related death worldwide, representing a global public health problem. This study evaluated nine patients with HCC. Six of the cases involved hepatic explants, and three involved hepatic segmentectomy for tumor resection. Eight out of nine tumors were HCC, with one being a combined hepatocellular-cholangiocarcinoma tumor. Conventional markers of hepatocellular differentiation (Hep Par-1, arginase, pCEA, and glutamine synthetase) were positive in all patients, while markers of hepatic precursor cells (CK19, CK7, EpCAM, and CD56) were negative in most patients, and when positive, they were detected in small, isolated foci. Based on in silico analysis of HCC tumors from The Cancer Genome Atlas database, we found that Hedgehog (HH) pathway components (GLI1, GLI2, GLI3 and GAS1) have high connectivity values (module membership > 0.7) and are strongly correlated with each other and with other genes in biologically relevant modules for HCC. We further validated this finding by analyzing the gene expression of HH components (PTCH1, GLI1, GLI2 and GLI3) in our samples through qPCR, as well as by immunohistochemical analysis. Additionally, we conducted a chemosensitivity analysis using primary HCC cultures treated with a panel of 18 drugs that affect the HH pathway and/or HCC. Most HCC samples were sensitive to sunitinib. Our results offer a comprehensive view of the molecular landscape of HCC, highlighting the significance of the HH pathway and providing insight into focused treatments for HCC.
In-depth experimental search for a coupling between gravity and electromagnetism with steady fields
Authors: Tajmar M. , Kößling M. , Neunzig O. 
Published: August 2024

AbstractAny means to control gravity like electromagnetism is currently out of reach by many orders of magnitude even under extreme laboratory conditions. Some often poorly executed experiments or pseudoscience theories appear from time to time claiming for example anomalous forces from capacitors that suggest a connection between the two fields. We developed novel and high resolution horizontal-, vertical- and rotation-balances that allow to test electric devices completely shielded and remotely controlled under high vacuum conditions to perform the first in-depth search for such a coupling using steady fields. Our testing included a variety of capacitors of different shapes and compositions as well as for the first-time solenoids and tunneling currents from Zener diodes and varistors. A comprehensive coupling-scheme table was used to test almost all combinations including capacitors and solenoids with permittivity and permeability gradients as well as capacitors and varistors within crossed magnetic fields. We also tested a crossed-coil producing helical magnetic field lines as well as interactions between a pair of shielded toroidal coils to look for proposed extensions to Maxwell’s equations. No anomalous forces or torques down to the nano-Newton or nano-Newton-Meter range were found providing new limits many orders of magnitude below previous assessments ruling out claims or theories and providing a basis for future research on the topic.
Design of a self-regulating mRNA gene circuit
Authors: Dykeman Eric C. 
Published: August 2024

AbstractProtein expression in vivo is predominately controlled via regulatory feedback mechanisms that adjust the level of mRNA transcription. However for positive sense single-stranded RNA viruses, protein expression is often controlled via secondary structural elements, such as internal ribosomal entry sites, that are encoded within the mRNA. The self-regulation of mRNA translation observed in this class of viruses suggests that it may be possible to design mRNAs that self-regulate their protein expression, enabling the creation of mRNAs for vaccines and other synthetic biology applications where protein levels in the cell can be tightly controlled without feedback to a transcriptional mechanism. As a proof of concept, I design a polycistronic mRNA based on bacteriophage MS2, where the upstream gene is capable of repressing synthesis of the downstream gene. Using a computational tool that simulates ribosome kinetics and the co-translational folding of the mRNA in response, I show that mutations to the mRNA can be identified which enhance the efficiency of the translation and the repression of the downstream gene. The results of this study open up the possibility of designing bespoke mRNA gene circuits in which the amount of protein synthesised in cells are self-regulated for therapeutic or antigenic purposes.
Whole genome sequencing analysis of Mycobacterium tuberculosis reveals circulating strain types and drug-resistance mutations in the Philippines
Authors: Wang Linfeng , Lim Dodge R. , Phelan Jody E. , Reyes Lorenzo T. , Palparan Alma G. , Sanchez Maria Guileane C. , Asuncion Louella Abigail A. , Tujan Ma. Angelica A. , Medado Inez Andrea P. , Daga Chona Mae A. , Llames Jo-Hannah S. , Mitarai Satoshi , Murase Yoshiro , Morishige Yuta , Ang Concepcion F. , Malabad John Carlo M. , Montoya Jaime C. , Hafalla Julius C. , Campino Susana , Hibberd Martin L. , Ama Cecilia G. , Basilio Ramon P. , La Paz Eva Maria Cutiongoco-De , Clark Taane G. 
Published: August 2024

AbstractThe Philippines is a high-incidence country for tuberculosis, with the increasing prevalence of multi- (MDR-TB) and extensively-drug (XDR-TB) resistant Mycobacterium tuberculosis strains posing difficulties to disease control. Understanding the genetic diversity of circulating strains can provide insights into underlying drug resistance mutations and transmission dynamics, thereby assisting the design of diagnostic tools, including those using next generation sequencing (NGS) platforms. By analysing genome sequencing data of 732 isolates from Philippines drug-resistance survey collections spanning from 2011 to 2019, we found that the majority belonged to lineages L1 (531/732; 72.5%) and L4 (European-American; n = 174; 23.8%), with the Manila strain (L1.2.1.2.1) being the most prominent (475/531). Approximately two-thirds of isolates were found to be at least MDR-TB (483/732; 66.0%), and potential XDR-TB genotypic resistance was observed (3/732; 0.4%), highlighting an emerging problem in the country. Genotypic resistance was highly concordant with laboratory drug susceptibility testing. By finding isolates with (near-)identical genomic variation, five major clusters containing a total of 114 isolates were identified: all containing either L1 or L4 isolates with at least MDR-TB resistance and spanning multiple years of collection. Closer inspection of clusters revealed transmission in prisons, some involving isolates with XDR-TB, and mutations linked to third-line drug bedaquiline. We have also identified previously unreported mutations linked to resistance for isoniazid, rifampicin, ethambutol, and fluoroquinolones. Overall, this study provides important insights into the genetic diversity, transmission and circulating drug resistance mutations of M. tuberculosis in the Philippines, thereby informing clinical and surveillance decision-making, which is increasingly using NGS platforms.