julilili42/papers huggingface dataset:
Automated remote speech‐based testing of individuals with cognitive decline: Bayesian agreement of transcription accuracy
2024-10-01

Abstract Introduction We investigated the agreement between automated and gold‐standard manual transcriptions of telephone chatbot‐based semantic verbal fluency testing. Methods We examined 78 cases from the Screening over Speech in Unselected Populations for Clinical Trials in AD (PROSPECT‐AD) study, including cognitively normal individuals and individuals with subjective cognitive decline, mild cognitive impairment, and dementia. We used Bayesian Bland–Altman analysis of word count and the qualitative features of semantic cluster size, cluster switches, and word frequencies. Results We found high levels of agreement for word count, with a 93% probability of a newly observed difference being below the minimally important difference. The qualitative features had fair levels of agreement. Word count reached high levels of discrimination between cognitively impaired and unimpaired individuals, regardless of transcription mode. Discussion Our results support the use of automated speech recognition particularly for the assessment of quantitative speech features, even when using data from telephone calls with cognitively impaired individuals in their homes. Highlights High levels of agreement were found between automated and gold‐standard manual transcriptions of telephone chatbot‐based semantic verbal fluency testing, particularly for word count. The qualitative features had fair levels of agreement. Word count reached high levels of discrimination between cognitively impaired and unimpaired individuals, regardless of transcription mode. Automated speech recognition for the assessment of quantitative and qualitative speech features, even when using data from telephone calls with cognitively impaired individuals in their homes, seems feasible and reliable.
Recurrent tick bites induce high IgG1 antibody responses to α‐Gal in sensitized and non‐sensitized forestry employees in Luxembourg
2024-10-01

Abstract Background The α‐Gal syndrome (AGS) is characterized by the presence of specific IgE‐antibodies to the carbohydrate galactose‐α‐1,3‐galactose (α‐Gal). Sensitization to α‐Gal has been associated with tick bites and individuals exposed to ticks have an elevated risk of sensitization. The aim of this study was to analyze IgG and IgE antibody responses to α‐Gal in a high‐risk cohort of forestry employees (FE) in Luxembourg. Methods Questionnaires and serum samples of FE from Luxembourg ( n = 219) were retrospectively analyzed. α‐Gal specific IgE was quantified by ImmunoCAP, α‐Gal specific IgG and subclasses IgG 1–4 were determined by ELISA. Additionally, sera from population‐based controls ( n = 150) and two groups of food‐allergic patients, patients with AGS ( n = 45) and fish‐allergic patients ( n = 22) were assessed for IgG antibody responses to α‐Gal and cod extract. Results Twenty‐one percent of FE was sensitized to α‐Gal (sIgE ≥ 0.1 kU A /L). Both sensitized and non‐sensitized FE exhibited high levels of α‐Gal specific IgG, IgG1 and IgG3 compared with controls, indicating a stimulation of IgG responses by recurrent tick bites, independent of the sensitization status. AGS patients had the highest levels of IgG1 and IgG2 antibodies, whereas the profile of fish‐allergic patients was similar to the profile of the controls for which anti‐α‐Gal responses were dominated by IgG2 antibodies. α‐Gal sIgG4 levels were either very low or undetectable in all groups. Conclusion Our study provides evidence for a continuous stimulation of α‐Gal related immune responses by repeated tick bites, translating into highly elevated levels of IgG1 antibodies directed against α‐Gal.
Cangrelor versus crushed ticagrelor in patients with acute myocardial infarction and cardiogenic shock: rationale and design of the randomised, double-blind DAPT-SHOCK-AMI trial
2024-10-01

Cardiogenic shock (CS) is a devastating and fatal complication of acute myocardial infarction (AMI). CS can affect the pharmacokinetics and pharmacodynamics of medications. The unique properties of cangrelor make it the optimal P2Y12 inhibitor for CS-AMI, in terms of both efficacy and safety. The DAPT-SHOCK-AMI trial (ClinicalTrials.gov: NCT03551964; EudraCT: 2018-002161-19) will assess the benefits of cangrelor in patients with an initial CS-AMI undergoing primary angioplasty. This randomised, multicentre, placebo-controlled trial of approximately 550 patients (with an allowed 10% increase) in 5 countries using a double-blind design will compare initial P2Y12 inhibitor treatment strategies in patients with CS-AMI of (A) intravenous cangrelor and (B) ticagrelor administered as crushed tablets at a loading dose of 180 mg. The primary clinical endpoint is a composite of all-cause death, myocardial infarction (MI), or stroke within 30 days. The main secondary endpoints are (1) the net clinical endpoint, defined as death, MI, urgent revascularisation of the infarct-related artery, stroke, or major bleeding as defined by the Bleeding Academic Research Consortium criteria; (2) cardiovascular-related death, MI, urgent revascularisation, or heart failure; (3) heart failure; and (4) cardiovascular-related death, all (1-4) within 1 year after study enrolment. A platelet reactivity study that tests the laboratory antiplatelet benefits of cangrelor, when given in addition to standard antiplatelet therapy, will be conducted using vasodilator-stimulated phosphoprotein phosphorylation. The primary laboratory endpoints are the periprocedural rate of onset and the proportion of patients who achieve effective P2Y12 inhibition. The DAPT-SHOCK-AMI study is the first randomised trial to evaluate the benefits of cangrelor in patients with CS-AMI.
Quantitative assessment of residual tumor is a strong and independent predictor of survival in methylated glioblastoma following radiochemotherapy with lomustine/temozolomide
2024-10-01

Abstract Background Maximum tumor resection improves overall survival (OS) in patients with glioblastoma. The extent of resection (EOR) is historically dichotomized. The response assessment in neuro-oncology (RANO) resects group recently proposed criteria for volumetry-based EOR assessment in patients that were treated according to Stupp ́s protocol. The purpose of this study was (1) to investigate the prognostic value of EOR in patients receiving combined chemotherapy with lomustine (CCNU)/temozolomide (TMZ), and (2) to analyze the prognostic performance of binary EOR assessment compared to volumetric assessment. Methods Seventy-eight patients with newly diagnosed MGMT-methylated GBM undergoing tumor resection followed by radiochemotherapy with CCNU/TMZ were included in this study. Residual contrast-enhancing (CE) tumor volume after the first resection was measured and its influence on OS and progression-free survival was analyzed using uni- and multivariable Cox regression analysis as well as two-sided log-rank test. Patients were divided into residual tumor volume (RTV) ≤1 cm3, &amp;gt;1–≤5 cm3, and &amp;gt;5 cm3 following the proposed criteria of the RANO resect group. Results Prolonged OS was associated with age &amp;lt;60 years, low RTV, and gross total resection. RTV had a superior prognostic value compared to binary EOR assessment. Patients with total or near total resection of CE tumor (≤ 1 cm3 RTV) showed prolonged OS (median 54.4 months, 95% CI: 46.94–not reached), with a 5-year survival rate of 49%. Conclusions Low RTV is associated with increased survival in glioblastoma patients undergoing radiochemotherapy with CCNU/TMZ. This study demonstrates the applicability of the recently proposed RANO resect criteria in this subgroup of patients.
Comparison of online adaptive and non-adaptive magnetic resonance image-guided radiation therapy in prostate cancer using dose accumulation
2024-10-01

Deformably accumulated OA-MRgRT using 20x3Gy in PC showed significant but small dosimetric differences comparted to conv-IGRT. Feasibility of a dose accumulation methodology was demonstrated, which may be relevant for evaluating future hypo-fractionated OA-MRgRT approaches.
Exploring Alternative Zinc-Binding Groups in Histone Deacetylase (HDAC) Inhibitors Uncovers DS-103 as a Potent Ethylhydrazide-Based HDAC Inhibitor with Chemosensitizing Properties
2024-10-01

In this work, we synthesized a series of peptoid-based HDAC inhibitors with variations in the linker region and zinc-binding groups. All compounds were investigated for their HDAC inhibition, antiplasmodial activity, and cytotoxicity against native and cisplatin-resistant carcinoma cell lines. The ethylhydrazide 20 (DS-103) proved to be the most effective compound in these primary screenings. DS-103 showed nanomolar inhibition of class I HDACs and of HDAC6 (class IIb). To further investigate the binding mode of DS-103, a crystal structure of DS-103 in complex with HDAC6 was obtained, which represents the first reported crystal structure of an alkylhydrazide in complex with an HDAC enzyme. Importantly, DS-103 completely reversed cisplatin resistance in two different platinum-resistant solid cancer cell lines and demonstrated strong synergism with cisplatin. The synergistic anticancer effects are mediated by increased DNA damage and p21 expression, resulting in caspase-mediated apoptosis and cell death.
Household income is associated with attack frequency, but not with the prevalence of headache: an analysis of self-reported headache in the general population in Germany
2024-10-01

Abstract Background Headache disorders are among the most prevalent neurological disorders worldwide. However, whether groups differing in socioeconomic position (SEP) are disproportionately affected by headache disorders has not yet been adequately clarified. Our aim was to analyse (1) the headache prevalence by socioeconomic position (SEP) and (2) the attack frequency by SEP in a German population-based adult sample. Methods Cross-sectional data from a random general population were used. The sample included N = 2,189 participants aged ≥ 18 years. SEP was measured using net equivalised income (NEI) and education. A binary logistic regression model tested the effect of SEP in predicting the prevalence of headache in general. Ordinal logistic regressions were modeled to predict the effect of SEP on the likelihood of attack frequency. Attack frequency was categorized in low frequency episodic headache (LFEH: 0–3 days per month), moderate frequency episodic headache (MFEH: 4–14 days per month) and chronic headache (CH: ≥ 15 days per month). Results Of the 2,189 participants, 891 reported headache in the last six months. Neither income nor education was associated with headache prevalence. However, significant differences between income groups were found for attack frequency. Compared to participants with NEI &gt; 150%, those with NEI &lt; 60% were 5.21 times more likely (95%CI 2.03, 13.36) to experience higher headache frequency, and those with NEI between 60 and 150% were 2.29 times more likely (95%CI 1.02, 5.11), with adjustments made for a set of potential confounders, including depressive symptoms. Conclusions To reduce headache attacks, it is essential to address both low- and middle-income groups affected by headaches. Universal public health prevention campaigns are particularly appropriate.
Stimulus-Stimulus Versus Stimulus-Valence Learning in Evaluative Conditioning: Insights on the Ecological Conditions of Unconditioned Stimulus Revaluation Effects
2024-10-01

Previous research into the influence of postconditioning revaluation of unconditioned stimuli (USs) on evaluative conditioning (EC) effects produced inconsistent results. One potential factor determining the sensitivity of EC to US revaluation is whether conditioned stimuli (CSs) get linked to valence (stimulus-valence learning) or the specific USs (stimulus-stimulus learning). The present research tested the ecological conditions of stimulus-valence learning and thereby US revaluation. In a sequential procedure, Experiment 1 paired CSs with either different USs of the same valence (one-to-many pairings) or the same US repeatedly (one-to-one pairings). Although EC effects were equally large, US revaluation effects and memory for CS-US pairings were reduced for one-to-many compared to one-to-one pairings. Experiments 2 and 3 presented one-to-many pairings in a forward versus backward manner but found the two versions of a sequential pairing procedure equally effective in inducing stimulus-valence learning. We present potential learning mechanisms underlying the outcomes and discuss approaches to their investigation.
Paper-based isotachophoretic preconcentration technique for low-cost determination of glyphosate
2024-10-01

Abstract Electrophoretic microfluidic paper-based analytical devices (e-μPADs) are promising for low-cost and portable technologies, but quantitative detection remains challenging. In this study, we develop a paper-based isotachophoretic preconcentration and separation method for the herbicide glyphosate as a model analyte. The device, consisting of two electrode chambers filled with leading and terminating electrolytes and a nitrocellulose strip as the separation carrier, was illuminated by a flat light source and operated with a voltage supply of 400 V. Detection was accomplished using a simple camera. Colorimetric detection was optimized through competitive complexation between glyphosate, copper ions, and pyrocatechol violet as a dye. The buffer system was optimized using simulations, (i) ensuring the pH was optimal for the demetallation of the blue pyrocatechol violet-copper complex [PV] to the yellow free dye and (ii) ensuring the electrophoretic migration of glyphosate into the slower [PV] for the colorimetric reaction. A new data evaluation method is presented, analyzing the RGB channel intensities. The linear range was between 0.8 and 25 μM, with a LOD of approximately 0 . 8 μM. The ITP separation preconcentrated glyphosate by a factor of 820 in numerical simulations. The method may be applied to control glyphosate formulations, especially in developing countries where herbicide sales and applications are poorly regulated. Graphical Abstract
Using SRG/eROSITA to predict soft proton induced ATHENA backgrounds
2024-10-01

Abstract Soft protons populating the space environment have affected the performance of the X-ray detectors on board Chandra and XMM-Newton, and they pose a threat for future high energy astrophysics missions with larger aperture, such as ATHENA. In this paper, we aim to predict the soft proton induced ATHENA backgrounds from the modelling of the orbital flux obtained using eROSITA on board SRG. To this end, we analysed the background measured by eROSITA and with the help of simulations we defined a range of values for the potential count-rate of quiet-time soft protons focused through the mirror shells. We used it to derive an estimate of the orbital soft proton flux, from which the induced background for the WFI and X-IFU detectors can be predicted, assuming ATHENA in the same L2-orbit as SRG. The scaling, based on the computed proton transmission yields of the optics and optical/thermal filters, indicates that the soft proton induced WFI and X-IFU backgrounds could be expected within the requirement. Regardless of where ATHENA will be placed (L1 or L2), our analysis also suggests that increasing somewhat the thickness of the WFI optical blocking filter, e.g. by <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mo>∼</mml:mo> </mml:math> 30%, would help to further reduce the soft proton flux onto the detector, which might be worth in case the planned magnetic diverters perform worse than expected due to soft proton neutralisation at the mirror level.
Straddling the Line Between In Vitro and Ex Vivo Investigations
2024-10-01

Tissue engineering research fundamentally relies on experiments to advance knowledge, utilizing various models for research on both humans and animals. With scientific progress, experimental models have become increasingly complex over time. This complexity sometimes blurs the distinction between categories, making terminology less consistent. In biomedical research, three overarching terms are commonly used to characterize experimental environments: <i>in vitro</i>, <i>ex vivo</i>, and <i>in vivo</i>. While <i>in vitro</i> translates from Latin as "in glass," referring historically to experimental conditions in a test tube or petri dish, <i>in vivo</i> experiments occur within a living organism's natural environment. Conversely, <i>ex vivo</i> originates from living tissue outside its host environment while striving to maintain conditions as close to the host surroundings as possible. In the tissue engineering and regenerative medicine (TE&RM) community, there needs to be more clarity between <i>in vitro</i> and <i>ex vivo</i> terminology, with historical definitions sometimes disregarded and new terms often introduced without rigorous scientific justification. At this juncture, the question arises of when to refer to experiments as <i>in vitro</i> or <i>ex vivo</i> or whether the terms may be used synonymously in some instances. Moreover, what criteria must <i>ex vivo</i> experiments meet to be legitimately defined as such? This perspective is intended to address questions that would assist the TE&RM community in better understanding the differences between <i>in vitro</i> and <i>ex vivo</i> models. Impact Statement In the tissue engineering & regenerative medicine literature, the terms "in vitro" and "ex vivo" are often used interchangeably to describe experiments. This interchangeable usage can lead to a compromised interpretation of research results and, consequently, misleading scientific conclusions and teachings. This perspective aims to provide clarity on the various definitions of experimental designs. It also highlights the issue of using terms with inconsistent meanings that have origins dating back to the distant past. It's important to note that scientific definitions constantly evolve, and there is a scientifically rooted responsibility to evaluate and rethink the current state of affairs critically.
RUFCO: A Deep Learning Framework to Postprocess Subseasonal Precipitation Accumulation Forecasts
2024-10-01

Abstract Postprocessing is a critical step in attaining calibrated and reliable probabilistic forecast output from numerical weather prediction models. A novel deep learning framework is proposed to postprocess 20 years of 7- and 14-day precipitation accumulation reforecasts from the Global Ensemble Forecast System at subseasonal time scales (week 1, week 2, and combined weeks 3–4 forecasts) over the contiguous United States. The network builds upon previous studies and is a combination of three parallel-trained components suitable for subseasonal prediction. The first is a ResUnet architecture which learns nonlinear relationships between binned observed precipitation and input images of weather and geographical variables. The second conditions the network to the month-of-year via a feature-wise linear modulation (FiLM) layer. The third helps the network learn when to revert the forecast to that of climatology. The RUFCO (named for its components ResUnet, FiLM, and Climatological-Offramp) forecasts are compared against raw and climatological forecasts as well as those from a state-of-the-art distributional regression postprocessing model, “censored, shifted gamma distribution (CSGD),” and a simple bias-corrected model. At week 1, every method exhibited a competitive advantage over climatological forecasts. At week 2, RUFCO generated forecasts with statistically significant improvement over climatology at 82%–94% of the domain, beating CSGD’s coverage of 76%–90% of the grid points. At week 3, RUFCO’s skillful coverage was 65%–85%, while CSGDs dropped to only 12%–37%. At the longer lead times, RUFCO achieved the highest domain-averaged skill scores across seasons. However, the network tends to “smooth” forecast skill, making it less competitive with CSGD in limited areas with strongly spatially varying biases. Significance Statement Precipitation accumulation forecasts 1, 2, and 3–4 weeks in advance are increasingly in-demand for a variety of decision-making applications around hydrologic forecasting, flood and drought awareness, and wildfire preparedness. However, raw forecasts from numerical weather prediction systems have errors that hinder skill. Postprocessing methods remove those errors and provide more reliable and skillful forecasts. We show that a new neural network technique is an effective and competitive postprocessing tool compared to more traditional techniques.
Arithmetic counts of tropical plane curves and their properties
2024-10-01

Abstract Recently, the first and third author proved a correspondence theorem which recovers the Levine- Welschinger invariants of toric del Pezzo surfaces as a count of tropical curves weighted with arithmetic multiplicities. In this paper, we study properties of the arithmetic count ofplane tropical curves satisfying point conditions. We prove that this count is independent of the configuration of point conditions. Moreover, a Caporaso- Harris formula for the arithmetic count of plane tropical curves is obtained by moving one point to the very left. Repeating this process until all point conditions are stretched, we obtain an enriched count of floor diagrams which coincides with the tropical count. Finally, we prove polynomiality properties for the arithmetic counts using floor diagrams.
Factors Associated With Smoking Cessation in Pregnancy
2024-10-01

Abstract: Background: Smoking during pregnancy poses a major health risk to pregnant smokers and their children. Pregnancy could be an opportune moment for cessation. Yet many smokers do not quit during pregnancy. This study aims to explore potential influencing factors for successful smoking cessation in pregnancy. Methods: Cross-sectional data was collected in an anonymous online survey (n=358). Data of n=60 women between the 24th week of pregnancy and four months postpartum was analysed. Variables showing significant differences between women who successfully quit smoking during pregnancy (“ex-smokers”, n=40) and women who were still smoking at the time of the survey (“smokers”, n=20) were included in a logistic regression to identify potentially important influencing factors. Results: Ex-smokers showed higher education levels, were employed, had a planned pregnancy, abstained from alcohol during pregnancy, and scored lower on the Fagerström test for cigarette dependence. They showed greater satisfaction with life and higher scores on the personality trait “agreeableness”. In the regression model, a planned pregnancy, alcohol abstinence and higher agreeableness scores increased the odds of being an ex-smoker. Conclusions: Planned pregnancies could be particularly suitable for smoking cessation. Alcohol should be considered, as abstinence could contribute to smoking cessation. A personality characterised by high agreeableness could be beneficial at least in addition to other factors.
Behavioral and Emotional Academic Procrastination Scale
2024-10-01

Abstract: The Behavioral and Emotional Procrastination Scale ( Bobe et al., 2022 ) measures the general frequency of behavioral and emotional components of academic procrastination. We used a representatively stratified sample of students based on demographic data from the Federal Statistical Office (2021 ) to provide extended evidence for the scale’s reliability and validity of test score interpretation and generate normative values. Our quota sample consisted of 890 students. We addressed deviations from the population with weighting factors. We found evidence for the reliability of the subscales delay and subjective discomfort, the assumed factorial structure, and measurement invariance regarding gender, field of study, type of university, and study phase. Motivational costs were significantly positively related to delay, and delay and subjective discomfort were significantly associated with academic performance and study satisfaction. The normative values quantify the extent of the components of academic procrastination to support researchers and practitioners in helping students overcome them.