bluuebunny/crossref_metadata_2025_split huggingface dataset:
Promising efficacy of immune checkpoint inhibitor plus chemotherapy for thoracic SMARCA4-deficient undifferentiated tumor
Authors: Lin Ying , Yu Bo , Sun Haifeng , Zhang Hongyu , Hu Zhihuang , Zhang Yao , Wu Zhenhua , Sun Si , Zhao Xinmin , Yu Hui , Wu Xianghua , Li Yuan , Wang Jialei , Wang Huijie 
Published: April 2023

Abstract
Purpose
Thoracic SMARCA4-deficient undifferentiated tumor (SD-UT) is a highly aggressive disease that is nosologically related to but distinct from SMARCA4-deficient non-small cell lung cancer (SD-NSCLC). No standard treatment guidelines were established for SD-UT. This research explored the efficacy of different treatments in SD-UT, and the prognostic, clinicopathologic and genomic difference between SD-UT and SD-NSCLC.

Materials and methods
Information of 25 SD-UT and 22 SD-NSCLC patients diagnosed and treated in Fudan University Shanghai Cancer Center from January, 2017 to September, 2022 was analyzed.

Results
SD-UT was similar to SD-NSCLC in characteristics of onset age, male prevalence, heavy smoking history and metastatic pattern. SD-UT showed a rapid relapse pattern after radical therapy. For Stage IV SD-UT patients, immune checkpoint inhibitor (ICI) plus chemotherapy significantly improved median progression-free survival (PFS) compared to traditional chemotherapy as first-line treatment (26.8 vs. 2.73 months, p = 0.0437), while objective response rates of two arms were comparable (71.4% vs. 66.7%). No significant survival differences were observed between SD-UT and SD-NSCLC under similar treatment settings. SD-UT or SD-NSCLC patients receiving ICI in the first line had significantly prolonged OS than those with ICI in the latter lines or without ICI treatment throughout clinical courses. Genetic study found frequent SMARCA4, TP53 and LRP1B mutations in SD-UT.

Conclusion
To the best of our knowledge, this is the largest series to date to compare the efficacy of ICI-based treatment to chemotherapy and document frequent mutations of LRP1B in SD-UT. ICI plus chemotherapy is an effective strategy for Stage IV SD-UT.
The omics era: a nexus of untapped potential for Mendelian chromatinopathies
Authors: Nava Aileen A. , Arboleda Valerie A. 
Published: April 2023

AbstractThe OMICs cascade describes the hierarchical flow of information through biological systems. The epigenome sits at the apex of the cascade, thereby regulating the RNA and protein expression of the human genome and governs cellular identity and function. Genes that regulate the epigenome, termed epigenes, orchestrate complex biological signaling programs that drive human development. The broad expression patterns of epigenes during human development mean that pathogenic germline mutations in epigenes can lead to clinically significant multi-system malformations, developmental delay, intellectual disabilities, and stem cell dysfunction. In this review, we refer to germline developmental disorders caused by epigene mutation as “chromatinopathies”. We curated the largest number of human chromatinopathies to date and our expanded approach more than doubled the number of established chromatinopathies to 179 disorders caused by 148 epigenes. Our study revealed that 20.6% (148/720) of epigenes cause at least one chromatinopathy. In this review, we highlight key examples in which OMICs approaches have been applied to chromatinopathy patient biospecimens to identify underlying disease pathogenesis. The rapidly evolving OMICs technologies that couple molecular biology with high-throughput sequencing or proteomics allow us to dissect out the causal mechanisms driving temporal-, cellular-, and tissue-specific expression. Using the full repertoire of data generated by the OMICs cascade to study chromatinopathies will provide invaluable insight into the developmental impact of these epigenes and point toward future precision targets for these rare disorders.
Gut microbiota composition and function in pregnancy as determinants of prediabetes at two-year postpartum
Authors: Houttu Noora , Benchraka Chouaib , Lotankar Mrunalini , Muhli Ella , Niinikoski Harri , Lahti Leo , Laitinen Kirsi 
Published: April 2023

Abstract
Aims
Deep metagenomics offers an advanced tool for examining the relationship between gut microbiota composition and function and the onset of disease; in this case, does the composition and function of gut microbiota during pregnancy differ in women who develop prediabetes and those who do not at two-year postpartum, and whether the gut microbiota composition associates with glycemic traits.

Methods
In total, 439 women were recruited in early pregnancy. Gut microbiota was assessed by metagenomics analysis in early (13.9 ± 2.0 gestational weeks) and late pregnancy (35.1 ± 1.0 gestational weeks). Prediabetes was determined using American Diabetes Association criteria as fasting plasma glucose 5.6–6.9 mmol/l analyzed by an enzymatic hexokinase method. Of the women, 39 (22.1%) developed prediabetes by two-year postpartum.

Results
The relative abundances of Escherichia unclassified (FDR < 0.05), Clostridiales bacterium 1_7_ 47FAA (FDR < 0.25) and Parabacteroides (FDR < 0.25) were higher, and those of Ruminococcaceae bacterium D16 (FDR < 0.25), Anaerotruncus unclassified (FDR < 0.25) and Ruminococcaceae noname (FDR < 0.25) were lower in early pregnancy in those women who later developed prediabetes. In late pregnancy, Porphyromonas was higher and Ruminococcus sp 5_1_39BFAA was lower in prediabetes (FDR < 0.25). Furthermore, fasting glucose concentrations associated inversely with Anaerotruncus unclassified in early pregnancy and directly with Ruminococcus sp 5_1_39BFAA in late pregnancy (FDR < 0.25). α-Diversity or β-diversity did not differ significantly between the groups. Predictions of community function during pregnancy were not associated with prediabetes.

Conclusions
Our study shows that some bacterial species during pregnancy contributed to the onset of prediabetes within two-year postpartum. These were attributable primarily to a lower abundance of short-chain fatty acids-producing bacteria.
Plasma concentrations of anti-inflammatory cytokine TGF-β are associated with hippocampal structure related to explicit memory performance in older adults
Authors: Raschick Matthias , Richter Anni , Fischer Larissa , Knopf Lea , Schult Annika , Yakupov Renat , Behnisch Gusalija , Guttek Karina , Düzel Emrah , Dunay Ildiko Rita , Seidenbecher Constanze I. , Schraven Burkhart , Reinhold Dirk , Schott Björn H. 
Published: April 2023

AbstractHuman cognitive abilities, and particularly hippocampus-dependent memory performance typically decline with increasing age. Immunosenescence, the age-related disintegration of the immune system, is increasingly coming into the focus of research as a considerable factor contributing to cognitive decline. In the present study, we investigated potential associations between plasma levels of pro- and anti-inflammatory cytokines and learning and memory performance as well as hippocampal anatomy in young and older adults. Plasma concentrations of the inflammation marker CRP as well as the pro-inflammatory cytokines IL-6 and TNF-α and the anti-inflammatory cytokine TGF-β1 were measured in 142 healthy adults (57 young, 24.47 ± 4.48 years; 85 older, 63.66 ± 7.32 years) who performed tests of explicit memory (Verbal Learning and Memory Test, VLMT; Wechsler Memory Scale, Logical Memory, WMS) with an additional delayed recall test after 24 h. Hippocampal volumetry and hippocampal subfield segmentation were performed using FreeSurfer, based on T1-weighted and high-resolution T2-weighted MR images. When investigating the relationship between memory performance, hippocampal structure, and plasma cytokine levels, we found that TGF-β1 concentrations were positively correlated with the volumes of the hippocampal CA4–dentate gyrus region in older adults. These volumes were in turn positively associated with better performance in the WMS, particularly in the delayed memory test. Our results support the notion that endogenous anti-inflammatory mechanisms may act as protective factors in neurocognitive aging.
Correlation analysis of agricultural drought risk on wet farming crop and meteorological drought index in the tropical-humid region
Authors: Irawan Amalia Nafisah Rahmani , Komori Daisuke , Hendrawan Vempi Satriya Adi 
Published: April 2023

AbstractIn the tropical-humid region, wet farming crops (e.g., paddy) are a common agricultural commodity with a high-water requirement. Usually planted in the Asia monsoon region with a high precipitation rate, these crops are divided into the wet cropping season and the dry cropping season. During the dry cropping season, they are particularly vulnerable to agricultural drought caused by the decrease in precipitation. This study used Indonesia as a case study and is aimed at assessing the agricultural drought risk on a wet farming crop during the dry cropping season by examining the correlation between the drought hazard and its risk. For hazard assessment, Standardized Precipitation Index (SPI) was used to assess the agricultural drought, by using the Global Satellite Mapping of Precipitation (GSMaP) which has 0.1° × 0.1° spatial resolution. The result of correlation analysis between the SPI and drought-affected areas on a city scale showed that SPI-3 in August is the most suitable timescale to assess the agricultural drought in Indonesia. The agricultural drought risk assessment was conducted on the grid scale, where the crop yield estimation model was developed with the help of Normalized Difference Vegetation Index (NDVI). Based on the correlation analysis between SPI-3 and the detrended crop yield as drought risk indicators, the higher yield loss was found in the area above the threshold value (r-value ≤ 0.6) indicating that those areas were more vulnerable to drought, while the area below the threshold value has lower crop yield loss even in the area that was hit by the most severe drought, because the existing irrigation system was able to resist the drought’s impact on crop yield loss.
On the homeotypes of kobellite
Authors: Makovicky Emil , Balić-Žunić Tonči 
Published: April 2023

AbstractKobellite is a Pb-Bi-Sb sulfosalt with minor amounts of (Cu, Fe) and with the crystal structure composed of two types of rods, one of which has unusual lateral extensions (‘lobes’), which depart from the usual lozenge-shaped rod cross-section in sulfosalts. Several Pb-Bi-Sb and Pb-Sb-rich sulfosalts form a small group built on similar principles. Some of them are related by homology (e.g., izoklakeite), and differ by the perpendicular dimensions of rods (length and multiplicity of atomic layers in a rod; e.g., sterryite), and especially by different combinations of archetypes and archetype portions which participate in the rods (PbS archetype and the two orientations of SnS archetype). The present article summarizes and discusses the published data on the group. Homeotypism makes the group interesting and potentially a fertile source of further structural varieties.
Association of medication clusters and subsequent labor market marginalization in refugee and Swedish-born young adults with common mental disorders in Sweden
Authors: Chen J. , Mittendorfer-Rutz E. , Taipale H. , Rahman S. , Niederkrotenthaler T. , Klimek P. 
Published: April 2023

AbstractLittle is known about the association between common mental disorders (CMD) and labor market integration among refugee and Swedish-born young adults. Socially disadvantaged patients such as refugees are more likely to discontinue their medication use prematurely. This study aimed to identify clusters of individuals with similar psychotropic medication patterns; and examine the relationship between cluster membership with labor market marginalization (LMM) in refugee and Swedish-born young adults with CMD. The study uses a longitudinal matched cohort aged 18-24 years with CMD diagnoses from Swedish registers covering 2006–2016. Dispensed psychotropic medications (antidepressants, antipsychotics, anxiolytics, sedative-hypnotics, mood stabilizers) were collected one year before and after CMD diagnosis. Clusters of patients with similar time courses of prescribed dosages were algorithmically identified. The association of cluster membership with subsequent LMM, (long-term sickness absence, SA, disability pension, DP, or long-term unemployment, UE) was assessed using Cox regression. Among 12,472 young adults with CMD, there were 13.9% with SA, 11.9% with DP, and 13.0% with UE during a mean follow-up of 4.1 years (SD 2.3 years). Six clusters of individuals were identified. A cluster with a sustained increase in all medication types yielded the highest hazard ratio (HR [95% CI]) 1.69 [1.34, 2.13] for SA and 2.63 [2.05, 3.38] for DP. The highest HRs of UE give a cluster with a concentrated peak in antidepressants at CMD diagnosis (HR 1.61[1.18, 2.18]). Refugees and Swedish-born showed similar associations between clusters and LMM. To prevent LMM, targeted support and early assessment of CMD treatment are needed for individuals with a sustained increase in psychotropic medication after CMD diagnosis and for refugees in high-risk clusters for UE characterized by a rapid lowering of treatment dosages, which could be an indicator for premature medication discontinuation.
Detecting deception using machine learning with facial expressions and pulse rate
Authors: Tsuchiya Kento , Hatano Ryo , Nishiyama Hiroyuki 
Published: April 2023

AbstractGiven the ongoing COVID-19 pandemic, remote interviews have become an increasingly popular approach in many fields. For example, a survey by the HR Research Institute (PCR Institute in Survey on hiring activities for graduates of 2021 and 2022. https://www.hrpro.co.jp/research_detail.php?r_no=273. Accessed 03 Oct 2021) shows that more than 80% of job interviews are conducted remotely, particularly in large companies. However, for some reason, an interviewee might attempt to deceive an interviewer or feel difficult to tell the truth. Although the ability of interviewers to detect deception among interviewees is significant for their company or organization, it still strongly depends on their individual experience and cannot be automated. To address this issue, in this study, we propose a machine learning approach to aid in detecting whether a person is attempting to deceive the interlocutor by associating the features of their facial expressions with those of their pulse rate. We also constructed a more realistic dataset for the task of deception detection by asking subjects not to respond artificially, but rather to improvise natural responses using a web camera and wearable device (smartwatch). The results of an experimental evaluation of the proposed approach with 10-fold cross-validation using random forests classifier show that the accuracy and the F1 value were in the range between 0.75 and 0.8 for each subject, and the highest values were 0.87 and 0.88, respectively. Through the analysis of the importance of the features the trained models, we revealed the crucial features of each subject during deception, which differed among the subjects.
Automatic generation of incremental taxonomies for supporting the users in the development of an RPA project
Authors: Martínez-Rojas Antonio , Barba Irene , Del Valle Carmelo , Jiménez-Ramírez Andrés , González-Enríquez José 
Published: April 2023

AbstractThe robotic process automation (RPA) paradigm is a discipline that is becoming increasingly popular thanks to the great interest shown by the industry. In such context, RPA solutions based on artificial intelligence, i.e., cognitive solutions, are receiving increasing attention. In a cognitive RPA project, the RPA developer is in charge of selecting the most suitable components that solve specific tasks from the sets of components provided by different RPA platforms. This selection is very challenging, especially since there is no homogeneity in component names or component classifications. Such a situation turns an RPA project’s development into a time-consuming, error-prone, and very tedious process. Therefore, supporting the RPA developer in developing a cognitive RPA project is desired. The industry has also pointed out this need. This work presents a proposal for supporting the users in developing a cognitive RPA project. To be more precise, an incremental method to automatically generate taxonomies from cognitive RPA platforms is proposed. Such taxonomies can be dynamically adapted when necessary. In previous work, the initial aspects of this research were presented. However, the current work greatly enhances such previous work by: (1) extending the proposed method to improve the management of real-world use cases from industry, (2) developing a proof-of-concept tool that is based on the proposed approach, (3) validating the proposed method by applying it to real-world use cases from industry, and (4) performing a literature review on related topics. The results obtained are auspicious and demonstrate that the proposed approach substantially improves the support given to users during the development of a cognitive RPA project.
Using psychological characteristics of situations for social situation comprehension in support agents
Authors: Kola Ilir , Jonker Catholijn M. , Riemsdijk M. Birna van 
Published: April 2023

AbstractSupport agents that help users in their daily lives need to take into account not only the user’s characteristics, but also the social situation of the user. Existing work on including social context uses some type of situation cue as an input to information processing techniques in order to assess the expected behavior of the user. However, research shows that it is important to also determine themeaningof a situation, a step which we refer to as social situation comprehension. We propose using psychological characteristics of situations, which have been proposed in social science for ascribing meaning to situations, as the basis for social situation comprehension. Using data from user studies, we evaluate this proposal from two perspectives. First, from a technical perspective, we show that psychological characteristics of situations can be used as input to predict the priority of social situations, and that psychological characteristics of situations can be predicted from the features of a social situation. Second, we investigate the role of the comprehension step in human–machine meaning making. We show that psychological characteristics can be successfully used as a basis for explanations given to users about the decisions of an agenda management personal assistant agent.
Empirically evaluating flaky test detection techniques combining test case rerunning and machine learning models
Authors: Parry Owain , Kapfhammer Gregory M. , Hilton Michael , McMinn Phil 
Published: April 2023

AbstractA flaky test is a test case whose outcome changes without modification to the code of the test case or the program under test. These tests disrupt continuous integration, cause a loss of developer productivity, and limit the efficiency of testing. Many flaky test detection techniques are rerunning-based, meaning they require repeated test case executions at a considerable time cost, or are machine learning-based, and thus they are fast but offer only an approximate solution with variable detection performance. These two extremes leave developers with a stark choice. This paper introduces CANNIER, an approach for reducing the time cost of rerunning-based detection techniques by combining them with machine learning models. The empirical evaluation involving 89,668 test cases from 30 Python projects demonstrates that CANNIER can reduce the time cost of existing rerunning-based techniques by an order of magnitude while maintaining a detection performance that is significantly better than machine learning models alone. Furthermore, the comprehensive study extends existing work on machine learning-based detection and reveals a number of additional findings, including (1) the performance of machine learning models for detecting polluter test cases; (2) using the mean values of dynamic test case features from repeated measurements can slightly improve the detection performance of machine learning models; and (3) correlations between various test case features and the probability of the test case being flaky.
Exploring Knowledge and Awareness of HCV Infection and Screening Test: A Cross-Sectional Survey Among an Italian Sample
Authors: Lo Moro Giuseppina , Scaioli Giacomo , Vola Lorenzo , Guastavigna Laura , Frattin Roberta , De Vito Elisabetta , Bert Fabrizio , Siliquini Roberta 
Published: April 2023

AbstractAddressing HCV represents a public health priority, especially in Italy, which has the highest HCV prevalence in Europe. This study primarily aimed to explore knowledge about the HCV infection and awareness of the existence of the HCV screening test in Italy, before the implementation of awareness campaigns in 2022. An online cross-sectional survey was conducted (December 2021–January 2022). The primary outcomes were: Disease Knowledge Score (DKS), Prevention and Transmission Knowledge Score (PTKS) (for both: scoring from 0 to 100%, higher scores corresponded to higher knowledge), and being unaware of the existence of the HCV screening. The final sample consisted of 813 participants. The median DKS was 75% (IQR = 66.7–83.3), the median PTKS was 46.2% (IQR = 38.5–53.8), and 23.2% of participants were unaware of HCV screening. Higher education, health-related study or profession, history of accidental injuries, being affected by HCV and having actively searched for information on HCV had positive associations with DKS. LGBT males showed significantly lower DKS. Considering PTKS, participants affected by HCV the disease had a negative association with this score. Having a postgraduate education reduced the likelihood of not knowing about the HCV screening test, while having at least one family member affected by hepatitis C increased this probability. This study highlighted a concerning lack of knowledge about prevention and transmission, indicating a need for targeted education campaigns. The findings emphasized the importance of information and motivation and identified male LGBT + individuals as a vulnerable group with limited disease knowledge. Future research should concern the effectiveness of awareness campaigns.
Examining Motivations to Walk the Camino de Santiago: A Typology of Pilgrims
Authors: Brumec Snežana , Lavrič Miran , Naterer Andrej 
Published: April 2023

AbstractThe purpose of this article is to develop a comprehensive understanding of people’s motivations for going on the Camino de Santiago pilgrimage using qualitative and quantitative methods. The methodology comprised qualitative research based on content analysis of 32 travelogue testimonies and quantitative research based on an online survey of prospective pilgrims (N = 228). Three dimensions of motivation were identified using the following factor analyses: secular, spiritual, and religious. Then, a two-step cluster analysis was conducted to classify pilgrims into seven different types. The results revealed that pilgrims are not homogeneous in their motivations and that, except for two types with a total frequency of 4%, secular motivation is more or less present in all other types of prospective pilgrims. There are no “purely religious” pilgrims. Religious motivation always appears together with secular, spiritual, or, most often, both these forms of motivation. The findings suggest that secular motivation may be related to a need for exploration, the core motive underlying self-actualization.