bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mental health improvement after the COVID-19 pandemic in individuals with psychological distress
Authors: Reutter Mario , Hutterer Katharina , Gründahl Marthe , Gall Dominik , Dannlowski Udo , Domschke Katharina , Leehr Elisabeth J. , Lonsdorf Tina B. , Lueken Ulrike , Reif Andreas , Schiele Miriam A. , Zwanzger Peter , Pauli Paul , Hein Grit , Gamer Matthias 
Published: March 2024

AbstractThe COVID-19 pandemic and associated countermeasures had an immensely disruptive impact on people’s lives. Due to the lack of systematic pre-pandemic data, however, it is still unclear how individuals’ psychological health has been affected across this incisive event. In this study, we analyze longitudinal data from two healthy samples (N = 307) to provide quasi-longitudinal insight into the full trajectory of psychological burden before (baseline), during the first peak, and at a relative downturn of the COVID-19 pandemic. Our data indicated a medium rise in psychological strain from baseline to the first peak of the pandemic (d = 0.40). Surprisingly, this was overcompensated by a large decrease of perceived burden until downturn (d =  − 0.93), resulting in a positive overall effect of the COVID-19 pandemic on mental health (d = 0.44). Accounting for this paradoxical positive effect, our results reveal that the post-pandemic increase in mental health is driven by individuals that were already facing psychological challenges before the pandemic. These findings suggest that coping with acute challenges such as the COVID-19 pandemic can stabilize previously impaired mental health through reframing processes.
Allergenicity and structural properties of new Cor a 1 isoallergens from hazel identified in different plant tissues
Authors: Hendrich Julian M. , Reuter Andreas , Jacob Thessa P. , Kara Hatice , Amer Sherine , Rödel Katharina , Wöhrl Birgitta M. 
Published: March 2024

AbstractThe hazel allergen Cor a 1 is a PR-10 protein, closely related to the major birch pollen allergen Bet v 1. Hazel allergies are caused by cross-reactive IgE antibodies originally directed against Bet v 1. Despite the importance of PR-10 proteins in allergy development, their function and localization in the plant remain largely elusive. Therefore, the presence of Cor a 1 mRNA and proteins was investigated in different tissues, i.e., the female flower, immature and mature nuts, catkins, and pollen. Four yet unknown Cor a 1 isoallergens, i.e., Cor a 1.0501–1.0801, and one new Cor a 1.03 variant were discovered and characterized. Depending on the isoallergen, the occurrence and level of mRNA expression varied in different tissues, suggesting different functions. Interestingly, Cor a 1.04 previously thought to be only present in nuts, was also detected in catkins and pollen. The corresponding Cor a 1 genes were expressed in Escherichia coli. The purified proteins were analysed by CD and NMR spectroscopy. Immunoblots and ELISAs to determine their allergenic potential showed that the new proteins reacted positively with sera from patients allergic to birch, hazel and elder pollen and were recognized as novel isoallergens/variants by the WHO/IUIS Allergen Nomenclature Sub-Committee.
Phytochemical screening, HPLC analysis, antimicrobial and antioxidant effect of Euphorbia parviflora L. (Euphorbiaceae Juss.)
Authors: Adil Muhammad , Filimban Faten Zubair , Ambrin  , Quddoos Atifa , Sher Ayaz Ali , Naseer Muhammad 
Published: March 2024

AbstractPlant extracts are actively being used worldwide due to the presence of biologically active constituents helping in the preservation of food, and to aid against various diseases owing to their antimicrobial and antioxidant potential. The present research work was carried out to investigate the phytochemical constituents, antimicrobial activity, and antioxidant activity of different extracted samples of Euphorbia parviflora. Anti-microbial studies were carried out by Agar well diffusion while the DPPH method was employed for investigating anti-oxidant activity. Three samples from methanol, chloroform, and ethyl acetate extract were tested against five different bacterial strains comprising two species from Gram-negative bacteria i.e., Staphylococcus aureus and Bacillus subtilis and three species from Gram-positive bacteria i.e. Escherichia coli, Pseudomonas aeruginosa and Klebsiella pneumonia along two fungal strains i.e. Candida albicans and Aspergillus niger. The results of the qualitative phytochemical analysis showed that methanolic, chloroformic, and ethylacetate extract of Euphorbia parviflora consist of alkaloids, reducing sugars, flavonoids, terpenoids, tannins, and saponins. The total phenol and flavonoid content of E. parviflora showed that the methanolic extract of E. parviflora had a significantly higher total phenolic content (53.73 ± 0.30 mg of GAE/g) and flavonoid content (44.62 ± 0.38 mg of than other extracts. The content of total phenolic and flavonoids was more in methanolic extract as compared to other extracts of E. prolifera. The HPLC analysis showed that in the chloroform extract of E. parviflora Cinnamic acid (4.32 ± 2.89 mg/g) was dominant, in methanol extract quercetin (3.42 ± 2.89 mg/g) was dominant and in ethyl acetate extract of E. parviflora catechin (4.44 ± 2.89 mg/g) was found dominant. The antimicrobial activity revealed that amongst all the extracts the highest antibacterial activity was shown by methanolic extract against B. subtilis and Staphylococcus aureus as compared to the other extracts. The antioxidant activity revealed that methanolic extract of E. parviflora demonstrated higher antioxidant activity (82.42 ± 0.02) followed by chloroform extract (76.48 ± 0.08) at 150 µg/mL. The aim of this study was primarily to evaluate the potential of this plant as a reliable source of antimicrobials and antioxidants that may be used for the treatment of various infectious diseases in the future. The study provides evidence that this plant can act as a reliable source of antimicrobial and antioxidant agents and might be used against several infectious diseases.
Mix proportion and microscopic characterization of coal-based solid waste backfill material based on response surface methodology and multi-objective decision-making
Authors: Zhao Xinyuan , Yang Ke , He Xiang , Wei Zhen , Zhang Jiqiang , Yu Xiang 
Published: March 2024

AbstractThe mix proportion of multi-source coal-based solid waste (CSW) for underground backfilling affects transportation and support performance of backfill materials, and even the backfilling cost. In this study, the optimal mix proportion of desulfurization gypsum (DG), furnace bottom slag (FBS) and gasification fine slag (GFS) is determined by the Response Surface Methodology–Box Behnken Design (RSM-BBD). Then the fluidity, bleeding rate, 3-day strength, 7-day strength and preparation cost are evaluation indicators, the optimal mix proportion of backfill materials is determined by the multi-objective decision-making method (MDM). Finally, the microstructure of the backfill material with optimal mix proportion was studied by TGA, MIP, SEM–EDS and XRD. The results show that the mix proportion of CSW with the optimal comprehensive index is coal gangue (CG): coal fly ash (CFA): DG: FBS: GFS = 1:1.5:0.2:0.1:0.1, the mass concentration is 78%, and ordinary Portland cement (OPC)/CSW = 7.5%. The weight loss phenomenon of the backfill material with the optimal mix proportion occurs continuously during the heating process, mainly due to the evaporation of crystal water, structural water and hydroxyl water. There are dense narrow-necked pores in the backfill material, and the pore connectivity is poor. There is no hydration reaction occurs between CSW particles, and the strength increase of the backfill material mainly depends on the hydration reaction of cement. In ettringite, part of Al2O3 is replaced by SiO2, and part of CaSO4 is replaced by CaCO3. This study provides a reference for the engineering application of underground backfilling with multi-source CSW.
Multimodal artificial intelligence-based pathogenomics improves survival prediction in oral squamous cell carcinoma
Authors: Vollmer Andreas , Hartmann Stefan , Vollmer Michael , Shavlokhova Veronika , Brands Roman C. , Kübler Alexander , Wollborn Jakob , Hassel Frank , Couillard-Despres Sebastien , Lang Gernot , Saravi Babak 
Published: March 2024

AbstractIn this study, we aimed to develop a novel prognostic algorithm for oral squamous cell carcinoma (OSCC) using a combination of pathogenomics and AI-based techniques. We collected comprehensive clinical, genomic, and pathology data from a cohort of OSCC patients in the TCGA dataset and used machine learning and deep learning algorithms to identify relevant features that are predictive of survival outcomes. Our analyses included 406 OSCC patients. Initial analyses involved gene expression analyses, principal component analyses, gene enrichment analyses, and feature importance analyses. These insights were foundational for subsequent model development. Furthermore, we applied five machine learning/deep learning algorithms (Random Survival Forest, Gradient Boosting Survival Analysis, Cox PH, Fast Survival SVM, and DeepSurv) for survival prediction. Our initial analyses revealed relevant gene expression variations and biological pathways, laying the groundwork for robust feature selection in model building. The results showed that the multimodal model outperformed the unimodal models across all methods, with c-index values of 0.722 for RSF, 0.633 for GBSA, 0.625 for FastSVM, 0.633 for CoxPH, and 0.515 for DeepSurv. When considering only important features, the multimodal model continued to outperform the unimodal models, with c-index values of 0.834 for RSF, 0.747 for GBSA, 0.718 for FastSVM, 0.742 for CoxPH, and 0.635 for DeepSurv. Our results demonstrate the potential of pathogenomics and AI-based techniques in improving the accuracy of prognostic prediction in OSCC, which may ultimately aid in the development of personalized treatment strategies for patients with this devastating disease.
Petrographical and petrophysical rock typing for flow unit identification and permeability prediction in lower cretaceous reservoir AEB_IIIG, Western Desert, Egypt
Authors: Abo Bakr Abdelraheim , El Kadi Hassan H. , Mostafa Taher 
Published: March 2024

AbstractThe primary objective of this study is to identify and analyze the petrophysical properties of the newly investigated AEB_IIIG member reservoir in Meleiha West Deep (MWD) Field and to classify it into different rock types. Additionally, this research intends to develop mathematical equations that may be utilized to estimate permeability in uncored sections of the same well or in other wells where core samples are unavailable. The analysis focused on the pore hole records of ten wells that were drilled in MWD Field. The reservoir levels were identified, and their petrophysical parameters were evaluated using well logs and core data. We were able to recognize seven different types of rocks (petrophysical static rock type 1 (PSRT1) to PSRT7) using petrography data, the reservoir quality index (RQI), the flow zone index (FZI), R35, hydraulic flow units (HFUs), and stratigraphy modified Lorenz (SML) plots. The analysis of the petrophysical data shows that AEB_IIIG has unsteady net pay thicknesses over the area. It has a range of 8–25% shale volume, 12–17% effective porosity, and 72–92% hydrocarbon saturation. The RQI results show that psrt1, psrt2 and psrt3 have a good reservoir quality as indicated by high R35 and helium porosity, respectively. They contribute with more than 75% of the reservoir production. The equation derived for each rock type of AEB_IIIG reservoir can be employed to forecast the permeability value distribution inside the reservoir.
Be prepared for interruptions: EEG correlates of anticipation when dealing with task interruptions and the role of aging
Authors: Ülkü Soner , Getzmann Stephan , Wascher Edmund , Schneider Daniel 
Published: March 2024

AbstractDealing with task interruptions requires the flexible use of working memory and attentional control mechanisms, which are prone to age-related changes. We investigated effects of age on dealing with task interruptions and potential advantages of anticipating an interruption using EEG and a retrospective cueing (retro-cue) paradigm. Thirty-two young (18–30 years) and 28 older (55–70 years) participants performed a visual working memory task, where they had to report the orientation of a target following a retro-cue. Within blocks of 10 trials, they were always, never, or randomly interrupted with an arithmetic task before the onset of the retro-cue. The interruption-induced decline in primary task performance was more pronounced in older participants, while only these benefited from anticipation. The EEG analysis revealed reduced theta and alpha/beta response to the retro-cue following interruptions, especially for the older participants. In both groups, anticipated interruptions were associated with increased theta and alpha/beta power prior and during the interruption, and stronger beta suppression to the retro-cue. The results indicate that interruptions impede the refocusing of attention on the task-relevant representation of the primary task, especially in older people, while anticipation facilitates preparation for the interruption task and resumption of the primary task.
Unraveling cradle-to-grave disease trajectories from multilayer comorbidity networks
Authors: Dervić Elma , Sorger Johannes , Yang Liuhuaying , Leutner Michael , Kautzky Alexander , Thurner Stefan , Kautzky-Willer Alexandra , Klimek Peter 
Published: March 2024

AbstractWe aim to comprehensively identify typical life-spanning trajectories and critical events that impact patients’ hospital utilization and mortality. We use a unique dataset containing 44 million records of almost all inpatient stays from 2003 to 2014 in Austria to investigate disease trajectories. We develop a new, multilayer disease network approach to quantitatively analyze how cooccurrences of two or more diagnoses form and evolve over the life course of patients. Nodes represent diagnoses in age groups of ten years; each age group makes up a layer of the comorbidity multilayer network. Inter-layer links encode a significant correlation between diagnoses (p < 0.001, relative risk > 1.5), while intra-layers links encode correlations between diagnoses across different age groups. We use an unsupervised clustering algorithm for detecting typical disease trajectories as overlapping clusters in the multilayer comorbidity network. We identify critical events in a patient’s career as points where initially overlapping trajectories start to diverge towards different states. We identified 1260 distinct disease trajectories (618 for females, 642 for males) that on average contain 9 (IQR 2–6) different diagnoses that cover over up to 70 years (mean 23 years). We found 70 pairs of diverging trajectories that share some diagnoses at younger ages but develop into markedly different groups of diagnoses at older ages. The disease trajectory framework can help us to identify critical events as specific combinations of risk factors that put patients at high risk for different diagnoses decades later. Our findings enable a data-driven integration of personalized life-course perspectives into clinical decision-making.
Diversity of sugar-diphospholipid-utilizing glycosyltransferase families
Authors: Meitil Ida K. S. , Gippert Garry P. , Barrett Kristian , Hunt Cameron J. , Henrissat Bernard 
Published: March 2024

AbstractPeptidoglycan polymerases, enterobacterial common antigen polymerases, O-antigen ligases, and other bacterial polysaccharide polymerases (BP-Pols) are glycosyltransferases (GTs) that build bacterial surface polysaccharides. These integral membrane enzymes share the particularity of using diphospholipid-activated sugars and were previously missing in the carbohydrate-active enzymes database (CAZy;www.cazy.org). While the first three classes formed well-defined families of similar proteins, the sequences of BP-Pols were so diverse that a single family could not be built. To address this, we developed a new clustering method using a combination of a sequence similarity network and hidden Markov model comparisons. Overall, we have defined 17 new GT families including 14 of BP-Pols. We find that the reaction stereochemistry appears to be conserved in each of the defined BP-Pol families, and that the BP-Pols within the families transfer similar sugars even across Gram-negative and Gram-positive bacteria. Comparison of the new GT families reveals three clans of distantly related families, which also conserve the reaction stereochemistry.
Identification and characterization of CIM-1, a carbapenemase that adds to the family of resistance factors against last resort antibiotics
Authors: Wang Yu , Sapula Sylvia A. , Whittall Jonathan J. , Blaikie Jack M. , Lomovskaya Olga , Venter Henrietta 
Published: March 2024

AbstractThe increasing rate of carbapenem-resistant bacteria within healthcare environments is an issue of great concern that needs urgent attention. This resistance is driven by metallo-β-lactamases (MBLs), which can catalyse the hydrolysis of almost all clinically available β-lactams and are resistant to all the clinically utilized β-lactamase inhibitors. In this study, an uncharacterized MBL is identified in a multidrug resistant isolate of the opportunistic pathogen, Chryseobacterium indologenes. Sequence analysis predicts this MBL (CIM-1) to be a lipoprotein with an atypical lipobox. Characterization of CIM-1 reveals it to be a high-affinity carbapenemase with a broad spectrum of activity that includes all cephalosporins and carbapenems. Results also shown that CIM-1 is potentially a membrane-associated MBL with an uncharacterized lipobox. Using prediction tools, we also identify more potentially lipidated MBLs with non-canonical lipoboxes highlighting the necessity of further investigation of lipidated MBLs.
Design, synthesis and biological evaluation of quinazoline and pyrrolo[3,2-d]pyrimidine derivatives as TLR7 agonists for antiviral agents
Authors: Song Yue , Fan Wenjie , Yao Chen , Wang Heng , Lu Xiuxiang , Wang Yumin , Liu Pengxiang , Ma Yanjie , Zhang Zhen , Wang Jiang , Chu BeiBei , Shi Lijun , Yang Guoyu , Wang Mengdi 
Published: March 2024

3 kinds of quinazoline derivatives and 5 kinds pyrrolo[3,2-d]pyrimidine derivatives targeting TLR7 were synthesized. The antiviral efficacy of these compounds was evaluated in vitro and in vivo.
Recovered supernova Ia rate from simulated LSST images
Authors: Petrecca V. , Botticella M. T. , Cappellaro E. , Greggio L. , Sánchez B. O. , Möller A. , Sako M. , Graham M. L. , Paolillo M. , Bianco F. ,   the LSST Dark Energy Science Collaboration
Published: March 2024

Aims. The Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) will revolutionize time-domain astronomy by detecting millions of different transients. In particular, it is expected to increase the number of known type Ia supernovae (SN Ia) by a factor of 100 compared to existing samples up to redshift ∼1.2. Such a high number of events will dramatically reduce statistical uncertainties in the analysis of the properties and rates of these objects. However, the impact of all other sources of uncertainty on the measurement of the SN Ia rate must still be evaluated. The comprehension and reduction of such uncertainties will be fundamental both for cosmology and stellar evolution studies, as measuring the SN Ia rate can put constraints on the evolutionary scenarios of different SN Ia progenitors.
Methods. We used simulated data from the Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) and LSST Data Preview 0 to measure the SN Ia rate on a 15 deg2 region of the “wide-fast-deep” area. We selected a sample of SN candidates detected in difference images, associated them to the host galaxy with a specially developed algorithm, and retrieved their photometric redshifts. We then tested different light-curve classification methods, with and without redshift priors (albeit ignoring contamination from other transients, as DC2 contains only SN Ia). We discuss how the distribution in redshift measured for the SN candidates changes according to the selected host galaxy and redshift estimate.
Results. We measured the SN Ia rate, analyzing the impact of uncertainties due to photometric redshift, host-galaxy association and classification on the distribution in redshift of the starting sample. We find that we are missing 17% of the SN Ia, on average, with respect to the simulated sample. As 10% of the mismatch is due to the uncertainty on the photometric redshift alone (which also affects classification when used as a prior), we conclude that this parameter is the major source of uncertainty. We discuss possible reduction of the errors in the measurement of the SN Ia rate, including synergies with other surveys, which may help us to use the rate to discriminate different progenitor models.
Perinatal Outcomes of Late Preterm Rupture of Membranes with or without Latency Antibiotics
Authors: Abu Nofal Mais , Massalha Manal , Diab Marwa , Abboud Maysa , Asla Jamhour Aya , Said Waseem , Talmon Gil , Mresat Samah , Mattar Kamel , Garmi Gali , Zafran Noah , Reiss Ari , Salim Raed 
Published: March 2024

Objective This study aimed to examine whether the addition of latency antibiotics in late preterm rupture of membranes (ROM) decreases neonatal infection and increases latency.
Study Design This retrospective two-center study was conducted at Holy Family Hospital (HFH) in Nazareth and Emek Medical Center (EMC) in Afula, on data collected between January 2017 and April 2023. HFH is the smaller institution. EMC and HFH implement similar policies regarding ROM at 340/7 to 366/7 weeks' gestation; the only difference is that a 10-day course of latency antibiotics is implemented at EMC. All women with ROM between 340/7 and 366/7 weeks' gestation who were admitted to one of the centers during the study period, and had a live fetus without major malformations, were included. The primary outcome was neonatal sepsis rate. Secondary outcomes included a composite of neonatal sepsis, mechanical ventilation ≥24 hours, and perinatal death. Additionally, gestational age at delivery and delivery mode were examined.
Results Overall, 721 neonates were delivered during the study period: 534 at EMC (where latency antibiotics were administered) and 187 at HFH. The gestational age at ROM was similar (35.8 and 35.9 weeks, respectively, p = 0.14). Neonatal sepsis occurred in six (1.1%) neonates at EMC and one (0.5%) neonate at HFH (adjusted p = 0.71; OR: 1.69; 95% Confidence Interval [CI]: 0.11–27.14). The composite secondary outcome occurred in nine (1.7%) and three (1.6%) neonates at EMC and HFH, respectively (adjusted p = 0.71; OR: 0.73; 95% CI: 0.14–3.83). The gestational age at delivery was 36.1 and 36.2 weeks at EMC and HFH, respectively (mean difference: 5 h; adjusted p = 0.02). The cesarean delivery rate was 24.7% and 19.3% at EMC and HFH, respectively (adjusted p = 0.96).
Conclusion Latency antibiotics administered to women admitted with ROM between 340/7 and 366/7 weeks' gestation did not decrease the rate of neonatal sepsis.
Key Points