bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Python-Based Laboratory
Authors: Essick John 
Published: December 2024

Abstract
The Python-Based Laboratory: A Hands-On Guide for Scientists and Engineers provides a learn-by-doing approach to acquiring the Python programming skills needed to implement computer-controlled experimental work. The Python-Based Laboratory leads its readers to mastery of the popular, open-source Python computer language in its role as a powerful laboratory tool by carrying out interesting and relevant projects that explore the acquisition, production, analysis, and presentation of digitized waveforms. Readers, who are assumed to have no prior computer programming or Python background, begin writing meaningful programs in the first few pages. The Python-Based Laboratory can be used as a textbook for science and engineering instructional laboratory students who are being taught up-to-date Python-based experimental skills. The book also works well as a self-study guide for professional laboratory researchers, industrial engineers, hobbyists, and electronics enthusiasts seeking to automate tasks using Python. Topics covered include the control of data-acquisition devices (including multifunction data-acquisition hardware and IEEE 488.2-interfaced stand-alone instruments), data file storage and presentation, digitized data concepts (such as resolution, sampling frequency, and aliasing), data analysis techniques (curve fitting and fast Fourier transform), and building a graphical user interface (GUI) using the Tkinter toolkit that is included as part of the Python Standard Library. As readers work their way through the book, they build several computer-based instruments, including a DC voltmeter, digital oscilloscope, DC voltage source, waveform generator, blinking LED array, digital thermometer, spectrum analyzer, and frequency meter. Each chapter concludes with a Do Yourself project and a Use It! example as well as a healthy selection of homework-style problems, allowing readers to test their understanding and further develop their Python-based experimentation skills.
Python Program Development
Authors: Essick John 
Published: December 2024

Abstract
This chapter focuses on writing a simple Python integer-parity-detector program that tests, and then reports, the parity (i.e., evenness or oddness) of an integer. Central features of Python are presented, including its programming environment (terminal session and IDLE program editor), data types, conditional branching, and exception (error) handling. In addition, Python’s support of object-oriented programming is introduced. A Do It Yourself project explores writing a Python program that accepts two numeric values as input, performs a mathematical calculation, and then outputs the result, while a Use It! example covers how to include comments within Python code as a means of program documentation.
Data Acquisition Using MCC DAQ Device
Authors: Essick John 
Published: December 2024

Abstract
After their Chapter 6 orientation to the MCC DAQ device’s capabilities via DAQami, readers write Python-based data-acquisition and generation programs that call functions from the Universal Library, MCC’s device driver software. These programs execute analog-to-digital and digital-to-analog tasks on the MCC DAQ device in order to realize several computer-based instruments, including a DC voltmeter, digital oscilloscope, DC voltage source, and (for upgraded MCC models) hardware-timed waveform generator. The necessity for placing GUI and DAQ operations on separate execution threads, as well as the need for triggering in an oscilloscope application, are explored. A Do It Yourself project implements the DAQ device’s digital outputs to create a blinking LED array, and a Use It! example demonstrates how a lowpass filter can effectively eliminate aliasing in the waveform-digitization process.
Data Analysis: Curve Fitting
Authors: Essick John 
Published: December 2024

Abstract
A thermistor is a semiconducting device commonly used as a temperature sensor. A physical model for a thermistor’s temperature-dependent resistance is presented and then readers write GUI-equipped Python programs that fit a thermistor’s temperature versus resistance calibration data to various functional forms consistent with the physical model. First, the NumPy library’s polynomial curve-fitting function is used to fit the data to a third-order polynomial. Next, the SciPy library’s more general nonlinear fitting function is used to fit the data to several alternate functions, including the widely used Steinhart–Hart equation. Goodness of the fitted curve is judged via residual plots. For the Do It Yourself project, readers utilize the thermistor’s fitted calibration curve, along with voltage values obtained across a thermistor using a DAQ device, to construct a computer-based digital thermometer. The Use It! example centers on using DAQ-device voltage readings to acquire thermocouple-based temperature measurements.
Control of Stand-Alone Instruments Using VISA
Authors: Essick John 
Published: December 2024

Abstract
Using the Python-based PyVISA and NI-VISA software drivers, control of an IEEE 488.2-interfaced stand-alone instrument over the Universal Serial Bus (USB) as well as the General Purpose Interface Bus (GPIB) is studied. The Agilent 34410A digital multimeter (which has the same command set as digital multimeters from other manufacturers) is used to demonstrate the central concepts of IEEE 488.2 interface-bus communication between a computer and stand-alone instrument, including synchronization (serial poll and service request) methods. Readers write GUI-equipped Python programs to control the instrument’s data-taking functions. In the latter portion of the chapter, reader create an instrument driver for the digital multimeter using the Python dictionary data structure as a lookup table for instrument specifications. A data logger is constructed and the procedure for configuring a LAN/Ethernet interface is described in a Do It Yourself project and Use It! example, respectively.
Humanized anti-CD11d monoclonal antibodies suitable for basic research and therapeutic applications
Authors: Blythe Eoin N , Barreira Christy , Fink Corby , Brown Arthur , Weaver Lynne C , Dekaban Gregory A 
Published: December 2024

Abstract

Background
Immunomodulatory agents targeting the CD11d/CD18 integrin are in development for the treatment of several pathophysiologies including neurotrauma, sepsis, and atherosclerosis. Murine anti-human CD11d therapeutic antibodies have successfully improved neurological and behavioral recovery in rodent neurotrauma models. Here, we present the progression of CD11d-targeted agents with the development of humanized anti-CD11d monoclonal antibodies.

Methods
Primary human leukocytes and the THP-1 monocytic cell line were used to determine the binding of the CD11d antibodies, determine binding affinities, and assess outside-in signaling induced by CD11d antibody binding. In addition, a rat model of spinal cord injury was employed to demonstrate that the humanized monoclonal antibodies retained their therapeutic function in vivo. These determinations were made using a combination of flow cytometry, western blotting, immunohistochemistry, biochemical assays, and a locomotor behavioral assessment.

Results
Flow cytometric analysis demonstrated that the humanized anti-CD11d clones bind both human monocytes and neutrophils. Using a THP-1 model, the humanized anti-CD11d-2 clone was then determined to bind both the active and inactive CD11d/CD18 conformations without inducing inflammatory cell signaling. Finally, an investigation using anti-CD11d-2 as a detection tool uncovered a mismatch between total and surface-level CD11d and CD18 expression that was not altered by CK2 inhibition.

Conclusions
By developing humanized anti-CD11d monoclonal antibodies, new tools are now available to study CD11d biology and potentially treat inflammation arising from acute neurotrauma via CD11d targeting.
Phytoliths in dicotyledons occurring in Northwest Europe: establishing a baseline
Authors: Hermans Rosalie , Strömberg Caroline A E , Löffelmann Tessi , Vrydaghs Luc , Speleers Lien , Chevalier Alexandre , Nys Karin , Snoeck Christophe 
Published: December 2024

Abstract

Background and Aims
The absence of a modern plant-based ‘dicotyledon’ phytolith reference baseline impedes the accurate interpretation of fossil phytolith records in archaeological and palaeoecological research within Northwest (NW) Europe. This study aims to fill this gap by documenting and analysing the phytolith record from modern dicotyledon taxa occurring in this region.

Methods
Phytoliths were extracted from several plant parts of 117 plant specimens representing 74 species (one or two specimens per species). The study employed light microscopy to examine phytolith production (non-producer, trace, common or abundant) and phytolith assemblage composition. The data were analysed statistically to (1) determine the influence of taxonomy and plant part on phytolith presence (absent/present) using a mixed model, (2) assess phytolith assemblage variation using a permutational multivariate analysis of variance (PerMANOVA) and (3) identify patterns among sample groups including segregation for plant part, life form (forbs vs. shrubs/trees) and order using linear discriminant analyses (LDA).

Key Results
Morphotype analysis revealed diagnostic morphotypes and features for specific plant families, genera and plant parts. LDA effectively segregated plant parts and life forms, though taxonomic groupings showed limited segregation. Phytolith presence (absent/present) was found to vary, influenced by both plant part and taxonomy. For species examined through two specimens, although phytolith production varied considerably, phytolith assemblage composition was consistent.

Conclusions
This study establishes a ‘dicotyledon’ phytolith baseline for NW Europe, showing that the phytolith record can be informative in terms of plant part and life form and that several phytolith morphotypes and/or features are taxonomically diagnostic below ‘dicotyledon’ level. The findings constitute a foundation upon which future research can build, refining and expanding our knowledge of the NW European region.
Purposive Placement: Autonomy Through Self-Lock-Up in Restrictive Housing Units
Authors: Rudes Danielle S , Magnuson Shannon , Ingel Sydney 
Published: December 2024

Abstract
The idea that some prison residents purposively seek placement within restricted housing units (RHUs) within US prisons is perhaps counter-intuitive. Prior scholarship acknowledges that some residents prefer RHUs for safety and solitude; however, scholars to date know very little about how and why RHU placement is purposively secured. The current study presents staff and resident interview data from four prisons within one US state. Findings suggest some residents intentionally seek the RHU for both precautionary and instrumental reasons and, in doing so, often work toward a goal of gaining some (if limited) autonomy. Findings also suggest that to attain RHU placement, residents purposively commit misconducts they know require RHU placement. These findings (1) suggest a need for general population and RHU reform and (2) showcase how residents use their limited autonomy to push back against institutional processes.
Deep learning-based patient stratification for prognostic enrichment of clinical dementia trials
Authors: Birkenbihl Colin , de Jong Johann , Yalchyk Ilya , Fröhlich Holger 
Published: December 2024

Abstract
Dementia probably due to Alzheimer’s disease is a progressive condition that manifests in cognitive decline and impairs patients’ daily life. Affected patients show great heterogeneity in their symptomatic progression, which hampers the identification of efficacious treatments in clinical trials. Using artificial intelligence approaches to enable clinical enrichment trials serves a promising avenue to identify treatments. In this work, we used a deep learning method to cluster the multivariate disease trajectories of 283 early dementia patients along cognitive and functional scores. Two distinct subgroups were identified that separated patients into ‘slow’ and ‘fast’ progressing individuals. These subgroups were externally validated and independently replicated in a dementia cohort comprising 2779 patients. We trained a machine learning model to predict the progression subgroup of a patient from cross-sectional data at their time of dementia diagnosis. The classifier achieved a prediction performance of 0.70 ± 0.01 area under the receiver operating characteristic curve in external validation. By emulating a hypothetical clinical trial conducting patient enrichment using the proposed classifier, we estimate its potential to decrease the required sample size. Furthermore, we balance the achieved enrichment of the trial cohort against the accompanied demand for increased patient screening. Our results show that enrichment trials targeting cognitive outcomes offer improved chances of trial success and are more than 13% cheaper compared with conventional clinical trials. The resources saved could be redirected to accelerate drug development and expand the search for remedies for cognitive impairment.
Improvement in quality of life in patients treated with lebrikizumab monotherapy is mediated by improvement in itch and sleep: Results from two Phase 3 trials in patients with moderate-to-severe atopic dermatitis
Authors: Yosipovitch Gil , de Bruin-Weller Marjolein , Wiseman Marni , Elberling Jesper , Gutermuth Jan , Pierce Evangeline , Montmayeur Sonia , Yang Fan Emily , Ding Yuxin , Bardolet Laia , Chisolm Sarah 
Published: December 2024

Abstract
Pruritus is a hallmark symptom of atopic dermatitis (AD) and is known to worsen patients’ health-related quality of life. Lebrikizumab is a high-affinity monoclonal antibody which binds IL-13, a dominant cytokine implicated in AD. This study includes data from two Phase 3 randomized controlled trials assessing the efficacy and safety of lebrikizumab in patients with moderate-to-severe AD, ADvocate1 (NCT04146363) and ADvocate2 (NCT04178967). We report a post-hoc analysis to quantify the effect of lebrikizumab vs placebo on the Dermatology Life Quality Index (DLQI) mediated indirectly through its effect on patient-reported outcomes itch and itch interference on sleep. Approximately two-thirds of the improvement in DLQI experienced by lebrikizumab-treated patients vs placebo-treated patients at Week 16 was mediated by improvement in itch and the interference of itch on sleep.
Increased phosphorescence of cyclometalated Ir(III) complex with a planar triarylborane moiety upon fluoride anion binding
Authors: Fukumoto Ryo , Sakuda Eri , Omoto Kenichiro , Horiuchi Shinnosuke , Arikawa Yasuhiro , Umakoshi Keisuke 
Published: December 2024

Abstract
A luminescent Ir(III) complex functionalized with a planar triarylborane moiety was prepared. This complex exhibits unique photophysical properties derived from the electron-withdrawing effect of the triarylborane moiety. A significant change in electron density occurs upon binding of F– to the electron-deficient boron center, resulting in decreased absorption and enhanced emission.
Supervised machine learning including environmental factors to predict in-hospital outcomes in acute heart failure patients
Authors: Sibilia Benjamin , Toupin Solenn , Bouali Nabil , Brette Jean-Baptiste , Ramonatxo Arthur , Schurtz Guillaume , Hamzi Kenza , Trimaille Antonin , Gall Emmanuel , Piliero Nicolas , Unger Alexandre , Andrieu Stéphane , Gonçalves Trecy , Picard Fabien , Roule Vincent , Roubille François , Houssany-Pissot Sonia , Bouchot Océane , Aboyans Victor , Vasram Reza Rossanaly , Bochaton Thomas , Logeart Damien , Solal Alain Cohen , Cartailler Jérôme , Mebazaa Alexandre , Dillinger Jean-Guillaume , Henry Patrick , Pezel Théo 
Published: December 2024

Abstract

Aims
While few traditional scores are available for risk stratification of patients hospitalized for acute heart failure (AHF), the potential benefit of machine learning (ML) is not well established. We aimed to assess the feasibility and accuracy of a supervised ML model including environmental factors to predict in-hospital major adverse events (MAEs) in patients hospitalized for AHF.

Methods and results
In April 2021, a French national prospective multicentre study included all consecutive patients hospitalized in intensive cardiac care unit. Patients admitted for AHF were included in the analyses. A ML model involving automated feature selection by least absolute shrinkage and selection operator (LASSO) and model building with a random forest (RF) algorithm was developed. The primary composite outcome was in-hospital MAE defined by death, resuscitated cardiac arrest, or cardiogenic shock requiring assistance. Among 459 patients included (age 68 ± 14 years, 68% male), 47 experienced in-hospital MAE (10.2%). Seven variables were selected by LASSO for predicting MAE in the training data set (n = 322): mean arterial pressure, ischaemic aetiology, sub-aortic velocity time integral, E/e′, tricuspid annular plane systolic excursion, recreational drug use, and exhaled carbon monoxide level. The RF model showed the best performance compared with other evaluated models [area under the receiver operating curve (AUROC) = 0.82, 95% confidence interval (CI) (0.78–0.86); precision-recall area under the curve = 0.48, 95% CI (0.42–0.5), F1 score = 0.56). Our ML model exhibited a higher AUROC compared with an existing score for the prediction of MAE (AUROC for our ML model: 0.82 vs. ACUTE HF score: 0.57; P &lt; 0.001).

Conclusion
Our ML model including in particular environmental variables exhibited a better performance than traditional statistical methods to predict in-hospital outcomes in patients admitted for AHF.

Study registration
ClinicalTrials.gov identifier: NCT05063097.
Mouse models of type I interferonopathies
Authors: Luca Domnica , Kato Hiroki 
Published: December 2024

Abstract
Type I interferonopathies are severe monogenic diseases caused by mutations that result in chronically upregulated production of type I interferon. They present with a broad variety of symptoms, the mechanisms of which are being extensively studied. Mouse models of type I interferonopathies are an important resource for this purpose, and in this context, we review several key molecular and phenotypic findings that are advancing our understanding of the respective diseases. We focus on genotypes related to nucleic acid metabolism, sensing by cytosolic receptors and downstream signalling.
Feasibility of 4D-flow CMR for haemodynamic characterization in hypertrophic cardiomyopathy after septal myectomy with and without anterior mitral valve leaflet extension
Authors: el Mathari Sulayman , van Ooij Pim , Merton Renske , Schrauben Eric , Hopman Luuk , Nederveen Aart , Götte Marco , Kluin Jolanda 
Published: December 2024

Abstract

OBJECTIVES
The common surgical treatment in patients with obstructive hypertrophic cardiomyopathy is septal myectomy. This involves resection of a segment of the myocardial septum and can be performed with and without concomitant anterior mitral valve leaflet extension (AMVLE). While both approaches have satisfying clinical outcomes, there is a lack of data regarding the added value of concomitant AMVLE. In particular, their impact on postoperative haemodynamics remains unexplored. Therefore, we conducted a study to assess the feasibility of utilizing four-dimensional-flow cardiac magnetic resonance imaging (4D-flow cardiac magnetic resonance imaging (CMR)) to investigate postoperative haemodynamic differences among both surgical approaches.

METHODS
In this feasibility study, nine subjects underwent 4D-flow CMR evaluation, including three patients who underwent isolated myectomy, three patients with myectomy + AMVLE and three healthy controls. Primary end-points were aortic wall shear stress, left ventricular outflow tract (LVOT) peak velocity and peak kinetic energy in the LVOT and ascending aorta.

RESULTS
Results showed that patients who underwent myectomy with concomitant AMVLE exhibited (i) lower aortic wall shear stress (−21.2%), (ii) lower LVOT peak velocity (−6.3%), (iii) higher kinetic energy in the LVOT (+10.8%) and (iv) lower kinetic energy in the ascending aorta (−28.8%) compared to patients who underwent isolated myectomy.

CONCLUSIONS
Patients undergoing additional AMVLE exhibited a better trend towards the haemodynamic reference values from healthy controls compared to patients undergoing isolated myectomy. Our findings underscore the feasibility of 4D-flow CMR to assess postoperative haemodynamic differences in hypertrophic cardiomyopathy patients undergoing different surgical approaches. This highlights the potential of 4D-flow CMR to compare surgical strategies based on postoperative haemodynamics.

Clinical registration number
Dutch National Medical Ethics Committee, registration number 2022.0078
Evaluating Sex Differences in Pneumococcal Disease Burden and Vaccination Effectiveness in Adults: A Population-Based Study
Authors: Forcadell-Peris María José , Vila-Córcoles Ángel , de Diego-Cabanes Cinta , Torras Vives Verònica , Ochoa-Gondar Olga , Satué-Gracia Eva M 
Published: December 2024

Abstract

Background
Information concerning sex differences in pneumococcal vaccine effectiveness in adults is scarce. The main aim of this study is to compare the differences in clinical effectiveness of pneumococcal vaccination between male and female.

Methods
This was a population-based cohort study involving 1 108 634 women and 951 011 men aged ≥50 years in Catalonia, Spain. Baseline characteristics of cohort members were established according to Institutional Research Database and pneumococcal disease-related hospitalizations (PDRH) captured from hospital discharge codes from 68 reference Catalonian hospitals during 2017–2018. Cox regression models were used to estimate PPsV23/PCV13 effectiveness against PDRH by sex.

Results
Across the 2-year follow-up, 4302 PDRH cases (1878 women, 2424 men) were observed, with incidences of 169.4/100 000 and 254.9/100 000 for women and men, respectively. Among women, neither PPsV23 (hazard ratio [HR], 1.04; 95% confidence interval [CI], .92–1.18; P = .540) or PCV13 (HR, 1.24; 95% CI, .91–1.70; P = .171) altered PDRH risk. Among men, PCV13 was associated with significantly increased risk of PDRH (HR, 1.57; 95% CI, 1.07–2.31; P = .021) whereas PPsV23 did not significantly alter this risk (HR, 0.89; 95% CI, .72–1.10; P = .275). No reduced risk of death following PDRH was observed in vaccinated women or men. However, regarding all-cause death, PPsV23 showed slight reduction in risk for women (HR, 0.94; 95% CI, .92–.97; P &lt; .001).

Conclusions
PPsV23/PCV13 vaccinations have not proven effective for either sex in preventing PDRH. PPsV23 appears associated with slight reduction risk of all-cause death in women, which could be related to better or longer-lasting vaccination effects in women compared to men.