bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prescribing carbonic anhydrase inhibitors to patients with “sulfa” antibiotics allergy: do we dare?
Authors: Quintanilla Raquel , van Leeuwen Luke , Sharma Arjun , Chang Ta Chen , Hodapp Elizabeth , McSoley John , Grajewski Alana , Bitrian Elena 
Published: February 2025

Abstract

Objective
To evaluate if provider characteristics affect attitude toward carbonic anhydrase inhibitors (CAI) prescription for patients with history of sulfonamide antibiotic (SA) hypersensitivity.

Methods
A survey querying providers’ attitudes toward CAI prescription in hypothetical patients with prior SA hypersensitivity was distributed to four ophthalmology and optometry organizations. Logistic regression was used to assess the relationship between avoiding CAI and profession, specialty, organizational affiliation, and years in practice.

Results
Of 250 respondents, 27% and 52% would avoid topical and oral CAI, respectively, in patients with prior SA rash and/or urticaria. >90% would avoid oral CAI in patients with prior severe SA hypersensitivity. Respondents with >10 years in practice were more likely to avoid oral CAI in patients with prior SA rash and/or urticaria than those with ≤10 (OR 2.27, p = 0.002). Respondents affiliated with non-glaucoma organizations were more likely to avoid oral CAI in patients with prior SA rash and/or urticaria than those affiliated with glaucoma organizations (p = 0.03). Providers without glaucoma training were more likely to avoid topical CAI in patients with prior SA rash and/or urticaria (p = 0.004) and anaphylaxis (p = 0.01) than glaucoma-trained providers.

Conclusions
Despite no supporting evidence, a significant number of respondents would avoid CAI in patients with prior SA hypersensitivity. Respondents without glaucoma training, no affiliation with a glaucoma organization, and >10 years in practice are more likely to avoid CAI in patients with type I SA hypersensitivity. Providers should be informed of the low cross-reactivity risk between CAI and SA so more patients may benefit from these drugs.
A systematic review of determinants of breast cancer risk among women with benign breast disease
Authors: Burke Aileen , O’Driscoll Jessica , Abubakar Mustapha , Bennett Kathleen E. , Carmody Emma , Flanagan Fidelma , Gierach Gretchen L. , Mullooly Maeve 
Published: February 2025

Abstract
Benign breast disease (BBD) is associated with heterogeneous breast cancer risk. Identifying key breast cancer risk factors for this population may inform breast cancer prevention or early detection strategies. We systematically searched literature databases PubMed, Embase, Scopus, Web of Science, and the Cochrane Library to identify studies reporting associations of demographic, lifestyle, reproductive, and radiological factors with risk of breast cancer among women with biopsy-confirmed BBD. 67 studies met eligibility criteria. Variation was observed for study time period, exposure measurement, comparison groups, outcomes, and adjustment for confounders, precluding meta-analysis. The literature suggested positive risk associations for age at biopsy, family history, mammographic breast density, and time since biopsy, and no association for body mass index, alcohol, smoking, age at menarche, and use of hormonal contraceptives. More research is needed to understand risk factor associations among women with BBD, particularly studies that account for heterogeneity within BBD and breast cancer.
Outlier-detection for reactive machine learned potential energy surfaces
Authors: Vazquez-Salazar Luis Itza , Käser Silvan , Meuwly Markus 
Published: February 2025

Abstract
Uncertainty quantification (UQ) to detect samples with large expected errors (outliers) is applied to reactive molecular potential energy surfaces (PESs). Three methods–Ensembles, deep evidential regression (DER), and Gaussian Mixture Models (GMM)—were applied to the H-transfer reaction between syn-Criegee and vinyl hydroxyperoxide. The results indicate that ensemble models provide the best results for detecting outliers, followed by GMM. For example, from a pool of 1000 structures with the largest uncertainty, the detection quality for outliers is ~90% and ~50%, respectively, if 25 or 1000 structures with large errors are sought. On the contrary, the limitations of the statistical assumptions of DER greatly impact its prediction capabilities. Finally, a structure-based indicator was found to be correlated with large average error, which may help to rapidly classify new structures into those that provide an advantage for refining the neural network.
Mathematical modeling of multicellular tumor spheroids quantifies inter-patient and intra-tumor heterogeneity
Authors: Malik Adam A. , Nguyen Kyle C. , Nardini John T. , Krona Cecilia C. , Flores Kevin B. , Nelander Sven 
Published: February 2025

Abstract
In the study of brain tumors, patient-derived three-dimensional sphere cultures provide an important tool for studying emerging treatments. The growth of such spheroids depends on the combined effects of proliferation and migration of cells, but it is challenging to make accurate distinctions between increase in cell number versus the radial movement of cells. To address this, we formulate a novel model in the form of a system of two partial differential equations (PDEs) incorporating both migration and growth terms, and show that it more accurately fits our data compared to simpler PDE models. We show that traveling-wave speeds are strongly associated with population heterogeneity. Having fitted the model to our dataset we show that a subset of the cell lines are best described by a “Go-or-Grow”-type model, which constitutes a special case of our model. Finally, we investigate whether our fitted model parameters are correlated with patient age and survival.
Transcriptomics and epigenomics datasets of primary brain cancers in formalin-fixed paraffin embedded format
Authors: García-Heredia Anabel , Guerra-Núñez Luna , Martín-Climent Paula , Rojas Estefanía , López-Domínguez Raúl , Alcántara-Domínguez Clara , Alenda Cristina , Valor Luis M. 
Published: February 2025

Abstract
The access of public omics-based datasets is of paramount importance in brain cancer research as allows the proposal and validation of both biomarkers and therapeutic targets in gliomas, especially in the most prevalent and aggressive glioblastomas. Taking profit of current advances in next generation sequencing and DNA methylation profiling, we have created datasets from approximately 150 formalin-fixed paraffin embedded (FFPE) tumours. These datasets enable for the first time integrative transcriptional and epigenetics studies in a context that consider the degradation and fixation-derived chemical alterations of the most extended archiving format in hospitals, and provide an independent cohort from current public databases for further validation of putative novel biomarkers. Alongside with the most profusely known glioblastomas, astrocytomas and oligodendrogliomas, we have also included for comparison purposes few examples of rare tumours that are often neglected in brain cancer research. Taken together, we provide a valuable tool to explore combined gene expression and DNA methylation patterns in the study of gliomas and glioneuronal tumours.
Machine learning enhanced grey box soft sensor for melt viscosity prediction in polymer extrusion processes
Authors: Perera Yasith S. , Li Jie , Abeykoon Chamil 
Published: February 2025

Abstract
Melt viscosity is regarded as a key quality indicator of the polymer melt in polymer extrusion processes. However, limitations such as disturbances to the melt flow and measurement delays of the existing in-line and side-stream rheometers prevent the monitoring and controlling of this key parameter in real time. Soft sensors can be employed to monitor physical parameters that are difficult to measure using hardware sensing instruments. This study presents a grey-box soft sensing solution to predict the melt viscosity in real time, which combines physics-based knowledge with machine learning. A fine-tuned physics-based mathematical model is used to make melt viscosity predictions, and a deep neural network is employed to compensate for its prediction errors. The proposed soft sensor model reported a normalised root mean square error of 2.2
$$\:\times\:$$
10−3 (0.22%), outperforming fully data-driven soft sensor models based on multilayer perceptron and long short-term memory neural networks. Furthermore, it exhibited an improvement of approximately 95% in terms of predictive performance, compared to a soft sensor based on a radial basis function neural network reported in a previous study. The proposed soft sensor can monitor viscosity changes caused by changes in operating conditions but not suitable for detecting viscosity changes due to changes in material properties. The findings of this study can aid in enhancing process monitoring and control in polymer extrusion processes.
Efficient WSI classification with sequence reduction and transformers pretrained on text
Authors: Pisula Juan I. , Bozek Katarzyna 
Published: February 2025

Abstract
From computer vision to protein fold prediction, Language Models (LMs) have proven successful in transferring their representation of sequential data to a broad spectrum of tasks beyond the domain of natural language processing. Whole Slide Image (WSI) analysis in digital pathology naturally fits to transformer-based architectures. In a pre-processing step analogous to text tokenization, large microscopy images are tessellated into smaller image patches. However, due to the massive size of WSIs comprising thousands of such patches, the problem of WSI classification has not been addressed via deep transformer architectures, let alone via available text-pre-trained deep transformer language models. We introduce SeqShort, a multi-head attention-based sequence shortening layer that summarizes a large WSI into a fixed- and short-sized sequence of feature vectors by removing redundant visual information. Our sequence shortening mechanism not only reduces the computational costs of self-attention on large inputs, it also allows to include standard positional encodings to the previously unordered bag of patches that compose a WSI. We use SeqShort to effectively classify WSIs in different digital pathology tasks using a deep, text pre-trained transformer model while fine-tuning less than 0.1% of its parameters, demonstrating that their knowledge about natural language transfers well to this domain.
Effect of neoadjuvant chemotherapy on CD14 + CD16 + monocytes and soluble CD163 in Egyptian breast cancer patients
Authors: Youssry Sara , Ghoneim Hossam , Barakat Riham , ElAlfy Eman 
Published: February 2025

Abstract
Neoadjuvant chemotherapy (NACT) influences the anticancer response by favourably altering the immune microenvironment. However, the effects of NACT on peripheral monocytes and their prognostic contribution to the NACT response have not yet been clarified. We aimed to evaluate the potential therapeutic responses and possible predictive value of double-positive (CD14 + CD16 +) monocytes and soluble CD163 (sCD163) in Egyptian breast cancer patients. Blood samples were obtained before and after neoadjuvant therapy from 30 patients with invasive breast cancer, and the expression of CD14 and CD16 was assessed via flow cytometry. The patients’ sCD163 levels were also determined in both the serum and culture supernatant using enzyme-linked immunosorbent assay (ELISA). The results revealed that NACT was associated with a significant decrease in double-positive monocytes and sCD163 levels. In addition, both double-positive monocytes and serum sCD163 were significantly associated with a partial clinical response. Double-positive monocytes and serum sCD163 levels may be related to therapeutic response, suggesting their possible predictive value in breast cancer patients receiving NACT.
Monocationic versus dicationic-based monomethine cyanine dyes for ultrasensitive colorimetric detection of hypochlorite ion in water
Authors: Hafez Nermeen S. , Amer Wael A. , Okba Ehab A. , Sakr Mahmoud A. S. , Alganzory Hussein H. , Khalil Sohaila M. , Ebeid El-Zeiny M. 
Published: February 2025

Abstract
Detecting residual chlorine as a hypochlorite ion (ClO−) in drinking water is crucial for ensuring disinfection effectiveness and safety. In the present study, we report two novel Quinolium Benzothiazole-Based Cyanine (3ethylbenzothiazol-2(3 H)-ylidene)methyl)-1-(4-iodobutyl)quinolin-1-ium tetrafluoroborate (IBTQ) and 1-(3-(4-(dimethylamino)pyridin-1-ium-1-yl)propyl)-4-((3-methylbenzothiazol-2(3 H)-ylidene)methyl)quinolin-1-ium diiodide (DMP-BTQ) hypochlorite (ClO−) sensors using UV- visible, colorimetric, and quartz crystal microbalance (QCM) techniques. The two sensors generate distinct absorption spectra, frequency shifts, and color changes that are visible to the naked eye. They exhibit high sensitivity and selectivity towards ClO−. The sensors have limits of detection (LOD) values in the range of 13.92 ppm and 0.127 ppm for IBTQ and DMP-BTQ, respectively, based on absorption performance with no interference of potential ions in drinking water. The method yields good recovery results, ranging from 97.4 to 103.0%, for ClO− detection in the studied water samples. In addition, the LOD for the QCM technique is 0.06 ppm for IBTQ and 0.045 ppm for DMP-BTQ with low quantification. The sensors can be loaded on paper strips for naked-eye detection of ClO− in domestic tap water and water treatment facilities. The sensors also provide low-cost, low cytotoxicity, high sensitivity, selectivity, and reusability of ClO− in water. The sensing mechanism was rationalized in terms of radical cation generation upon ClO− oxidizing action. The ease of cyanine oxidation was substantiated by quantum chemical studies including density functional theory (DFT) calculations, natural bond orbital (NBO) analysis, molecular electrostatic potential (MESP), and time-dependent density functional theory to support the experimental results.
A first report of Biomphalaria pfeifferi in the Lower Shire Valley, Southern Malawi, a major intermediate snail host species for intestinal schistosomiasis
Authors: Nkolokosa Clinton , Mbewe Rex , Chirombo James , Stanton Michelle C. , Jones Christopher M. , Makaula Peter , Namacha Gladys , Chiepa Blessings , Kalonde Patrick Ken , Baluwa Chifuniro , Zembere Kennedy , Kambewa Eggrey Aisha , Kaonga Chikumbusko Chiziwa , Archer John , Juhász Alexandra , Cunningham Lucas J. , Tangena Julie-Anne Akiko , Stothard J. Russell 
Published: February 2025

Abstract
The distribution of certain permissive intermediate snail host species in freshwater is a crucial factor shaping transmission of intestinal schistosomiasis, a neglected tropical disease that causes much human suffering in Africa. To shed new light on southern Malawi, where cases of intestinal schistosomiasis have been found, repeated malacological surveys were conducted in Chikwawa and Nsanje Districts in the Lower Shire Valley, to detect and to characterize populations of Biomphalaria, the intermediate host for intestinal schistosomiasis. Sampling took place across a total of 45 freshwater sites, noting water conductivity, pH, temperature, total dissolved salts (TDS) and geographical elevation. The presence or absence of snails was predicted upon physiochemical and environmental conditions in Random Forest modelling. Water conductivity, TDS and geographical elevation were most important in predicting abundance of snails with water temperature and pH of slightly less important roles. This first report of B. pfeifferi in the Lower Shire Valley enhances understanding of the environmental factors that strongly associate and allow prediction of its local distribution. This represents a useful step towards developing appropriate intervention strategies to mitigate intestinal schistosomiasis transmission.
Impact of the right ventricular mechanical pattern assessed by three-dimensional echocardiography on adverse outcomes following cardiac surgery
Authors: Keller Marius , Fábián Alexandra , Bandini Andrea , Szijártó Ádám , Tősér Zoltán , Merkely Béla , Heller Tim , Dürr Marcia-Marleen , Rosenberger Peter , Kovács Attila , Magunia Harry 
Published: February 2025

Abstract
Risk stratification for cardiac surgery is a cornerstone of perioperative management. While the prognostic impact of severe right ventricular (RV) dysfunction is well understood, the added value of the RV mechanical pattern regarding risk prediction remains unknown. We sought to prospectively validate the predictive value of 3D RV mechanics for adverse perioperative outcomes. The clinical and echocardiographic parameters of 439 retrospectively selected patients who underwent various types of cardiac surgery and 3D transesophageal echocardiography were investigated to determine their associations with a composite endpoint of an unfavorable postoperative outcome. Tricuspid regurgitation, 2D RV strains, and 3D measures of left ventricular (LV) and RV function were associated with the composite endpoint. Multivariable logistic regression models revealed that only tricuspid regurgitation, LV ejection fraction and 3D RV global longitudinal strain (GLS) were independently associated with the endpoint. By applying the model to the data of 128 prospectively enrolled patients, only 3D RV GLS remained an independent predictor. A RV GLS cutoff of -17.4% was found to be associated with a 3-fold increased risk for adverse outcomes. This led us to conclude that RV longitudinal deformation derived from 3D echocardiography is predictive of adverse outcomes and should be incorporated in perioperative risk stratification.
Social processing distorts physical distance perception
Authors: Michalareas Georgios , Lehr Claudia , Grabenhorst Matthias , Hecht Heiko 
Published: February 2025

Abstract
Psychopathy is traditionally linked to higher-level cognitive processes, but its impact on low-level cognitive functions has remained largely unexplored. This study investigates the relationship between the fundamental cognitive function of physical distance estimation and our social predisposition towards others, as captured by psychopathic traits, grouped into the three facets of Fearless Dominance, Self-Centered Impulsivity and Coldheartedness. Using an innovative experimental design, participants estimated the distance of an approaching avatar agent. We demonstrate that social processing, as reflected in the scale of Psychopathy in the general population, significantly distorts egocentric space perception. Strikingly, this distortion is absent with non-anthropomorphic agents. The study also reveals that agent emotional expressions do not affect distance estimation, when they are task-irrelevant, suggesting a disocciation between the effect of psychopathic traits on social processing and emotion processing. These results uncover a direct top-down effect of psychopathic traits on basic spatial cognition, in the presence of others. These new insights into the basic cognitive mechanisms underlying social interactions have broader implications for any field involving interpersonal spatial behaviour.
Distinct clinicopathological features and treatment differences in breast cancer patients of young age
Authors: Humlevik Rasmus O. C. , Svanøe Amalie A. , Aas Turid , Heie Anette , Sæle Anna K. M. , Akslen Lars A. , Wik Elisabeth , Hoivik Erling A. 
Published: February 2025

Abstract
The incidence of breast cancer in young women (aged under 40) is on the rise and is associated with more aggressive tumor characteristics and lower survival rates. Breast cancer is most frequently diagnosed in the sixth decade, and most research presents results based on data from older patients. By using large-scale clinico-pathologic and transcriptomic data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (n = 1932), we aimed to explore age-related differences in treatment, tumor characteristics, and gene expression signatures. Young patients presented more aggressive clinico-pathologic features such as higher histological grade, more frequent lymph node metastasis involvement, and estrogen receptor negativity. Accordingly, age below 40 years was associated with lower mRNA expression of the estrogen- and progesterone receptors, encoded by ESR1 and PGR, a higher proportion of the basal-like subtype, and increased transcription patterns reflecting stemness. Young breast cancer patients showed reduced survival, also within the basal-like subtype. We observed age-related differences in treatment, with more patients receiving chemotherapy among the young. Our results confirm a more challenging disease in young patients with breast cancer despite the more abundant use of chemotherapy. This argues for increased attention to young patients in current management and future research in breast cancer.
Artificial intelligence can extract important features for diagnosing axillary lymph node metastasis in early breast cancer using contrast-enhanced ultrasonography
Authors: Oshino Tomohiro , Enda Ken , Shimizu Hirokazu , Sato Megumi , Nishida Mutsumi , Kato Fumi , Oda Yoshitaka , Hosoda Mitsuchika , Kudo Kohsuke , Iwasaki Norimasa , Tanaka Shinya , Takahashi Masato 
Published: February 2025

Abstract
Contrast-enhanced ultrasound (CEUS) plays a pivotal role in the diagnosis of primary breast cancer and in axillary lymph node (ALN) metastasis. However, the imaging features that are clinically crucial for lymph node metastasis have not been fully elucidated. Hence, we developed a bimodal model to predict ALN metastasis in patients with early breast cancer by integrating CEUS images with the annotated imaging features. The model adopted a light-gradient boosting machine to produce feature importance, enabling the extraction of clinically crucial imaging features. In this retrospective study, the diagnostic performance of the model was investigated using 788 CEUS images of ALNs obtained from 788 patients who underwent breast surgery between 2013 and 2021, with the ground truth defined by the pathological diagnosis. The results indicated that the test cohort had an area under the receiver operating characteristic curve (AUC) value of 0.93 (95% confidence interval: 0.88, 0.98). The model had an accuracy of 0.93, which was higher than the radiologist’s diagnosis (accuracy of 0.85). The most important imaging features were heterogeneous enhancement, diffuse cortical thickening, and eccentric cortical thickening. Our model has an excellent diagnostic performance, and the extracted imaging features could be crucial for confirming ALN metastasis in clinical settings.
Biomarkers of inflammation in sweat after myocardial infarction
Authors: Björkenheim Anna , Sunnefeldt Erik , Finke Karl , Smith Daniel Robert , Fröbert Ole , Brasier Noé 
Published: February 2025

Abstract
ST-elevation myocardial infarction (STEMI) triggers a significant inflammatory response. Sweat may offer a novel, non-invasive medium for monitoring inflammation. In this prospective study, we characterized the inflammatory signatures in plasma and sweat collected from the skin surface of two patient groups: (1) 18 STEMI patients immediately following percutaneous coronary intervention (exposure) and (2) six patients who underwent outpatient angiography without subsequent intervention (control). Levels of 92 biomarkers were measured using a high-throughput proteomic assay and reassessed after 4–6 weeks in STEMI patients. Adjusting for patient group, sweat biomarkers did not show significant changes over time. In plasma, hepatocyte growth factor and interleukin-6 showed a significant decrease from the acute phase to follow-up, adjusted for patient group. STAM binding protein was significantly higher in the sweat of STEMI patients compared to controls, adjusted for time effects. While sweat was less sensitive than plasma for detecting biomarker levels in the setting of STEMI, its longitudinal analysis via wearable sensors holds promise for detecting specific markers.

Trial registration: The trial is registered on www.clinicaltrials.gov with the trial registration number NCT05843006.