bluuebunny/crossref_metadata_2025_split huggingface dataset:
KRT13 and UPK1B for differential diagnosis between metastatic lung carcinoma from oral squamous cell carcinoma and lung squamous cell carcinoma
Authors: Goda Hiroyuki , Nakashiro Koh-ichi , Sano Yoshifumi , Adachi Tomoko , Tokuzen Norihiko , Kuribayashi Nobuyuki , Hino Satoshi , Uchida Daisuke 
Published: December 2023

AbstractOral squamous cell carcinomas unusually show distant metastasis to the lung after primary treatment, which can be difficult to differentiate from primary squamous cell carcinoma of the lung. While the location and number of tumor nodules is helpful in diagnosing cases, differential diagnosis may be difficult even with histopathological examination. Therefore, we attempted to identify molecules that can facilitate accurate differential diagnosis. First, we performed a comprehensive gene expression analysis using microarray data for OSCC-LM and LSCC, and searched for genes showing significantly different expression levels. We then identified KRT13, UPK1B, and nuclear receptor subfamily 0, group B, member 1 (NR0B1) as genes that were significantly upregulated in LSCC and quantified the expression levels of these genes by real-time quantitative RT-PCR. The expression of KRT13 and UPK1B proteins were then examined by immunohistochemical staining. While OSCC-LM showed no KRT13 and UPK1B expression, some tumor cells of LSCC showed KRT13 and UPK1B expression in 10 of 12 cases (83.3%). All LSCC cases were positive for at least one of these markers. Thus, KRT13 and UPK1B might contribute in differentiating OSCC-LM from LSCC.
3-D breast nodule detection on automated breast ultrasound using faster region-based convolutional neural networks and U-Net
Authors: Oh Kangrok , Lee Si Eun , Kim Eun-Kyung 
Published: December 2023

AbstractMammography is currently the most commonly used modality for breast cancer screening. However, its sensitivity is relatively low in women with dense breasts. Dense breast tissues show a relatively high rate of interval cancers and are at high risk for developing breast cancer. As a supplemental screening tool, ultrasonography is a widely adopted imaging modality to standard mammography, especially for dense breasts. Lately, automated breast ultrasound imaging has gained attention due to its advantages over hand-held ultrasound imaging. However, automated breast ultrasound imaging requires considerable time and effort for reading because of the lengthy data. Hence, developing a computer-aided nodule detection system for automated breast ultrasound is invaluable and impactful practically. This study proposes a three-dimensional breast nodule detection system based on a simple two-dimensional deep-learning model exploiting automated breast ultrasound. Additionally, we provide several postprocessing steps to reduce false positives. In our experiments using the in-house automated breast ultrasound datasets, a sensitivity of $$93.65\%$$

93.65
%

with 8.6 false positives is achieved on unseen test data at best.
Evaluation of glomerular sirtuin-1 and claudin-1 in the pathophysiology of nondiabetic focal segmental glomerulosclerosis
Authors: Lopes-Gonçalves Guilherme , Costa-Pessoa Juliana Martins , Pimenta Ruan , Tostes Ana Flavia , da Silva Eloisa Martins , Ledesma Felipe Lourenço , Malheiros Denise Maria Avancini Costa , Zatz Roberto , Thieme Karina , Câmara Niels Olsen Saraiva , Oliveira-Souza Maria 
Published: December 2023

AbstractFocal segmental glomerulosclerosis (FSGS) is the leading cause of nephrotic syndrome, which is characterized by podocyte injury. Given that the pathophysiology of nondiabetic glomerulosclerosis is poorly understood and targeted therapies to prevent glomerular disease are lacking, we decided to investigate the tight junction protein claudin-1 and the histone deacetylase sirtuin-1 (SIRT1), which are known to be involved in podocyte injury. For this purpose, we first examined SIRT1, claudin-1 and podocin expression in kidney biopsies from patients diagnosed with nondiabetic FSGS and found that upregulation of glomerular claudin-1 accompanies a significant reduction in glomerular SIRT1 and podocin levels. From this, we investigated whether a small molecule activator of SIRT1, SRT1720, could delay the onset of FSGS in an animal model of adriamycin (ADR)-induced nephropathy; 14 days of treatment with SRT1720 attenuated glomerulosclerosis progression and albuminuria, prevented transcription factor Wilms tumor 1 (WT1) downregulation and increased glomerular claudin-1 in the ADR + SRT1720 group. Thus, we evaluated the effect of ADR and/or SRT1720 in cultured mouse podocytes. The results showed that ADR [1 µM] triggered an increase in claudin-1 expression after 30 min, and this effect was attenuated by pretreatment of podocytes with SRT1720 [5 µM]. ADR [1 µM] also led to changes in the localization of SIRT1 and claudin-1 in these cells, which could be associated with podocyte injury. Although the use of specific agonists such as SRT1720 presents some benefits in glomerular function, their underlying mechanisms still need to be further explored for therapeutic use. Taken together, our data indicate that SIRT1 and claudin-1 are relevant for the pathophysiology of nondiabetic FSGS.
Dual-level clustering ensemble algorithm with three consensus strategies
Authors: Shan Yunxiao , Li Shu , Li Fuxiang , Cui Yuxin , Chen Minghua 
Published: December 2023

AbstractClustering ensemble (CE), renowned for its robust and potent consensus capability, has garnered significant attention from scholars in recent years and has achieved numerous noteworthy breakthroughs. Nevertheless, three key issues persist: (1) the majority of CE selection strategies rely on preset parameters or empirical knowledge as a premise, lacking adaptive selectivity; (2) the construction of co-association matrix is excessively one-sided; (3) the CE method lacks a more macro perspective to reconcile the conflicts among different consensus results. To address these aforementioned problems, a dual-level clustering ensemble algorithm with three consensus strategies is proposed. Firstly, a backward clustering ensemble selection framework is devised, and its built-in selection strategy can adaptively eliminate redundant members. Then, at the base clustering consensus level, taking into account the interplay between actual spatial location information and the co-occurrence frequency, two modified relation matrices are reconstructed, resulting in the development of two consensus methods with different modes. Additionally, at the CE consensus level with a broader perspective, an adjustable Dempster–Shafer evidence theory is developed as the third consensus method in present algorithm to dynamically fuse multiple ensemble results. Experimental results demonstrate that compared to seven other state-of-the-art and typical CE algorithms, the proposed algorithm exhibits exceptional consensus ability and robustness.
Enhancing domain generalization in the AI-based analysis of chest radiographs with federated learning
Authors: Tayebi Arasteh Soroosh , Kuhl Christiane , Saehn Marwin-Jonathan , Isfort Peter , Truhn Daniel , Nebelung Sven 
Published: December 2023

AbstractDeveloping robust artificial intelligence (AI) models that generalize well to unseen datasets is challenging and usually requires large and variable datasets, preferably from multiple institutions. In federated learning (FL), a model is trained collaboratively at numerous sites that hold local datasets without exchanging them. So far, the impact of training strategy, i.e., local versus collaborative, on the diagnostic on-domain and off-domain performance of AI models interpreting chest radiographs has not been assessed. Consequently, using 610,000 chest radiographs from five institutions across the globe, we assessed diagnostic performance as a function of training strategy (i.e., local vs. collaborative), network architecture (i.e., convolutional vs. transformer-based), single versus cross-institutional performance (i.e., on-domain vs. off-domain), imaging finding (i.e., cardiomegaly, pleural effusion, pneumonia, atelectasis, consolidation, pneumothorax, and no abnormality), dataset size (i.e., from n = 18,000 to 213,921 radiographs), and dataset diversity. Large datasets not only showed minimal performance gains with FL but, in some instances, even exhibited decreases. In contrast, smaller datasets revealed marked improvements. Thus, on-domain performance was mainly driven by training data size. However, off-domain performance leaned more on training diversity. When trained collaboratively across diverse external institutions, AI models consistently surpassed models trained locally for off-domain tasks, emphasizing FL’s potential in leveraging data diversity. In conclusion, FL can bolster diagnostic privacy, reproducibility, and off-domain reliability of AI models and, potentially, optimize healthcare outcomes.
Cationic cellulose filter papers modified with ZnO/Ag/GO nanocomposite as point of use gravity-driven filters for bacterial removal from water
Authors: Ghaffari Seyed-Behnam , Sarrafzadeh Mohammad-Hossein 
Published: December 2023

AbstractThe surface modification of filters with large pore sizes for the development of low-cost gravity-driven point-of-use (POU) technologies for water disinfection can be an effective strategy to empower people to access safe water instantly, especially in low- and middle-income countries. In this study, the surface of commercial cellulose filter papers, as cheap and bio-based filters, was modified with polydopamine (PDA), polyethyleneimine (PEI) and ZnO/Ag/GO nanocomposite (ZnO/Ag/GO@PDA/PEI papers) for bacterial removal from water. PDA/PEI incorporation introduced a cationic functional layer, which can entrap negative bacteria and make a stable chemical bond with the nanocomposite. ZnO/Ag/GO exhibited promising synergistic antibacterial activities (30 times stronger than ZnO). As a result, 3 sheets of ZnO/Ag/GO@PDA/PEI papers showed a 99.98% bacterial reduction (E. coli), which met the WHO standards. Moreover, the leached zinc and silver in the filtrate were far below the WHO’s limits (380 and 10 ppb, respectively). The results showed that the modified papers could be reused multiple times. After six times of reuse, the flow rate dropped slightly (below 20%) and the bacterial removal efficiency was more than 99.9%. This study is valuable for developing filters for treating bacterial-contaminated water on-site with no need for energy, which is a demand in many countries.
Fourier tools for the evaluation of refractive multifocal designs
Authors: De Gracia Pablo 
Published: December 2023

AbstractThis paper presents innovative tools and methodologies for the theoretical assessment of optical properties in refractive multifocal designs. Utilizing lens segmentation techniques and classical Fourier optics, these tools can be of help evaluating multifocal contact lenses, intraocular lenses, small aperture designs, and corneal inlays. As an example of their utility, this study presents the through-focus Visual Strehl ratios in the frequency domain of 12 multifocal contact lenses from four companies, derived from the sagittal power profiles obtained with a NIMO equipment (LAMBDA-X) for three base prescriptions (− 6.00 D, − 3.00 D, and + 1.00 D). The contact lenses are also assessed alongside higher-order aberrations obtained from 65 eyes, measured using a Wavefront Sciences Complete Ophthalmic Analysis System (AMO). Diameter variations, corresponding to individual pupil sizes (2.45–6.27 mm), were considered in the evaluation. These novel tools enable the theoretical evaluation of multifocal solutions without the need for prototypes. In the case examples presented, they differentiate between lenses tailored for different presbyopic age groups, offer guidance on optimizing hyperfocal distance in contact lens design, and underscore the relevance of the effective aperture effect. Notably, this paper introduces the pioneering conversion of sagittal powers of multifocal solutions into an equivalent wavefront and optical quality metric, with potential applications in myopia control assessments. The author hopes that readers recognize and utilize these tools to advance the field of refractive multifocality.
Analysis of fracture-related infections from Swedish insurance claims between 2011 and 2021
Authors: Khalili Pendar , Tevell Staffan , Fischer Per , Hailer Nils P. , Wolf Olof 
Published: December 2023

AbstractFracture-related infections (FRI) pose a serious complication with an incidence of 1–2%. This study aimed to analyze compensation claims submitted to The Swedish National Patient Insurance Company (LÖF) because of FRI after closed/open reduction and internal fixation (C/ORIF) in the four most common fracture sites (proximal humerus, distal radius, hip, ankle). Patients registered in the LÖF database with a suspected FRI between 2011 and 2021 were identified by matching International Classification of Diseases and procedural codes indicative of a combination of fractures to the proximal humerus, distal radius, hip and ankle, C/ORIF and infection. Medical records were reviewed for fracture sites, pathogens and complications. Data from the Swedish Fracture Register (SFR) were extracted to estimate the proportion of reported claims to the presumed number of FRI. Of 122 FRI identified in the LÖF database, 34 were after C/ORIF in the proximal humerus, 12 in the distal radius, 28 in the hip and 48 in the ankle. LÖF compensated 111 patients (91%). Median time from C/ORIF to an FRI was 3 weeks (interquartile range 2–6), and 95% of all FRI occurred within 1 year after C/ORIF. Staphylococcus aureus was the most common pathogen in patients with a distal radius, hip and ankle FRI. In contrast, Cutibacterium spp. were the most common aetiology in FRI of the proximal humerus. The total number of fractures treated with C/ORIF in the four fracture sites registered in the SFR during 2021 was 18,711. Most of the FRI patients were diagnosed within the first year after C/ORIF, and 91% of the patients received compensation. Given an expected FRI incidence of 1–2%, our estimates with extrapolated data from the SFR indicate that < 10% of affected patients applied for compensation.
A retrospective study on machine learning-assisted stroke recognition for medical helpline calls
Authors: Wenstrup Jonathan , Havtorn Jakob Drachmann , Borgholt Lasse , Blomberg Stig Nikolaj , Maaloe Lars , Sayre Michael R. , Christensen Hanne , Kruuse Christina , Christensen Helle Collatz 
Published: December 2023

AbstractAdvanced stroke treatment is time-dependent and, therefore, relies on recognition by call-takers at prehospital telehealth services to ensure fast hospitalisation. This study aims to develop and assess the potential of machine learning in improving prehospital stroke recognition during medical helpline calls. We used calls from 1 January 2015 to 31 December 2020 in Copenhagen to develop a machine learning-based classification pipeline. Calls from 2021 are used for testing. Calls are first transcribed using an automatic speech recognition model and then categorised as stroke or non-stroke using a text classification model. Call-takers achieve a sensitivity of 52.7% (95% confidence interval 49.2–56.4%) with a positive predictive value (PPV) of 17.1% (15.5–18.6%). The machine learning framework performs significantly better (p < 0.0001) with a sensitivity of 63.0% (62.0–64.1%) and a PPV of 24.9% (24.3–25.5%). Thus, a machine learning framework for recognising stroke in prehospital medical helpline calls may become a supportive tool for call-takers, aiding in early and accurate stroke recognition.
Discovery and characterization of genes conferring natural resistance to the antituberculosis antibiotic capreomycin
Authors: Toh Shu-Ing , Elaine Keisha Johan , Wang Yung-Lin , Pan Yi-Chi , Jhu Yu-Heng , Hsiao Po-Yun , Liao Wen-Ting , Chen Po-Yuan , Ko Tai-Ming , Chang Chin-Yuan 
Published: December 2023

AbstractMetagenomic-based studies have predicted an extraordinary number of potential antibiotic-resistance genes (ARGs). These ARGs are hidden in various environmental bacteria and may become a latent crisis for antibiotic therapy via horizontal gene transfer. In this study, we focus on a resistance gene cph, which encodes a phosphotransferase (Cph) that confers resistance to the antituberculosis drug capreomycin (CMN). Sequence Similarity Network (SSN) analysis classified 353 Cph homologues into five major clusters, where the proteins in cluster I were found in a broad range of actinobacteria. We examine the function and antibiotics targeted by three putative resistance proteins in cluster I via biochemical and protein structural analysis. Our findings reveal that these three proteins in cluster I confer resistance to CMN, highlighting an important aspect of CMN resistance within this gene family. This study contributes towards understanding the sequence-structure-function relationships of the phosphorylation resistance genes that confer resistance to CMN.
The ER membrane protein complex restricts mitophagy by controlling BNIP3 turnover
Authors: Delgado Jose M , Shepard Logan Wallace , Lamson Sarah W , Liu Samantha L , Shoemaker Christopher J 
Published: December 2023

AbstractLysosomal degradation of autophagy receptors is a common proxy for selective autophagy. However, we find that two established mitophagy receptors, BNIP3 and BNIP3L/NIX, are constitutively delivered to lysosomes in an autophagy-independent manner. This alternative lysosomal delivery of BNIP3 accounts for nearly all its lysosome-mediated degradation, even upon mitophagy induction. To identify how BNIP3, a tail-anchored protein in the outer mitochondrial membrane, is delivered to lysosomes, we performed a genome-wide CRISPR screen for factors influencing BNIP3 flux. This screen revealed both known modifiers of BNIP3 stability as well as a pronounced reliance on endolysosomal components, including the ER membrane protein complex (EMC). Importantly, the endolysosomal system and the ubiquitin–proteosome system regulated BNIP3 independently. Perturbation of either mechanism is sufficient to modulate BNIP3-associated mitophagy and affect underlying cellular physiology. More broadly, these findings extend recent models for tail-anchored protein quality control and install endosomal trafficking and lysosomal degradation in the canon of pathways that tightly regulate endogenous tail-anchored protein localization.
Using CombiCells, a platform for titration and combinatorial display of cell surface ligands, to study T-cell antigen sensitivity modulation by accessory receptors
Authors: Patel Ashna , Andre Violaine , Eguiguren Sofia Bustamante , Barton Michael I , Burton Jake , Denham Eleanor M , Pettmann Johannes , Mørch Alexander M , Kutuzov Mikhail A , Siller-Farfán Jesús A , Dustin Michael L , van der Merwe P Anton , Dushek Omer 
Published: December 2023

AbstractUnderstanding cellular decisions due to receptor–ligand interactions at cell–cell interfaces has been hampered by the difficulty of independently varying the surface density of multiple different ligands. Here, we express the synthetic binder protein SpyCatcher, designed to form spontaneous covalent bonds with interactors carrying a Spytag, on the cell surface. Using this, we show that addition of different concentrations and combinations of native Spytag-fused ligands allows for the combinatorial display of ligands on cells within minutes. We use this combinatorial display of cell surface ligands—called CombiCells—to assess T cell antigen sensitivity and the impact of T cell co-stimulation and co-inhibition receptors. We find that the T cell receptor (TCR) displayed greater sensitivity to peptides on major-histocompatibility complexes (pMHC) than synthetic chimeric antigen receptor (CARs) and bi-specific T cell engager (BiTEs) display to their target antigen, CD19. While TCR sensitivity was greatly enhanced by CD2/CD58 interactions, CAR sensitivity was primarily but more modestly enhanced by LFA-1/ICAM-1 interactions. Lastly, we show that PD-1/PD-L1 engagement inhibited T cell activation triggered solely by TCR/pMHC interactions, as well as the amplified activation induced by CD2 and CD28 co-stimulation. The ability to easily produce cells with different concentrations and combinations of ligands should accelerate the study of receptor–ligand interactions at cell–cell interfaces.
TTLL12 is required for primary ciliary axoneme formation in polarized epithelial cells
Authors: Ceglowski Julia , Hoffman Huxley K , Neumann Andrew J , Hoff Katie J , McCurdy Bailey L , Moore Jeffrey K , Prekeris Rytis 
Published: December 2023

AbstractThe primary cilium is a critical sensory organelle that is built of axonemal microtubules ensheathed by a ciliary membrane. In polarized epithelial cells, primary cilia reside on the apical surface and must extend these microtubules directly into the extracellular space and remain a stable structure. However, the factors regulating cross-talk between ciliation and cell polarization, as well as axonemal microtubule growth and stabilization in polarized epithelia, are not fully understood. In this study, we find TTLL12, a previously uncharacterized member of the Tubulin Tyrosine Ligase-Like (TTLL) family, localizes to the base of primary cilia and is required for cilia formation in polarized renal epithelial cells. We also show that TTLL12 directly binds to the α/β-tubulin heterodimer in vitro and regulates microtubule dynamics, stability, and post-translational modifications (PTMs). While all other TTLLs catalyze the addition of glutamate or glycine to microtubule C-terminal tails, TTLL12 uniquely affects tubulin PTMs by promoting both microtubule lysine acetylation and arginine methylation. Together, this work identifies a novel microtubule regulator and provides insight into the requirements for apical extracellular axoneme formation.
Inflammasomes as regulators of mechano-immunity
Authors: Bezbradica Jelena S , Bryant Clare E 
Published: December 2023

AbstractMechano-immunity, the intersection between cellular or tissue mechanics and immune cell function, is emerging as an important factor in many inflammatory diseases. Mechano-sensing defines how cells detect mechanical changes in their environment. Mechano-response defines how cells adapt to such changes, e.g. form synapses, signal or migrate. Inflammasomes are intracellular immune sensors that detect changes in tissue and cell homoeostasis during infection or injury. We and others recently found that mechano-sensing of tissue topology (swollen tissue), topography (presence and distribution of foreign solid implant) or biomechanics (stiffness), alters inflammasome activity. Once activated, inflammasomes induce the secretion of inflammatory cytokines, but also change cellular mechanical properties, which influence how cells move, change their shape, and interact with other cells. When overactive, inflammasomes lead to chronic inflammation. This clearly places inflammasomes as important players in mechano-immunity. Here, we discuss a model whereby inflammasomes integrate pathogen- and tissue-injury signals, with changes in tissue mechanics, to shape the downstream inflammatory responses and allow cell and tissue mechano-adaptation. We will review the emerging evidence that supports this model.