bluuebunny/crossref_metadata_2025_split huggingface dataset:
Convergent evolution of plant pattern recognition receptors sensing cysteine-rich patterns from three microbial kingdoms
Authors: Yang Yuankun , Steidele Christina E. , Rössner Clemens , Löffelhardt Birgit , Kolb Dagmar , Leisen Thomas , Zhang Weiguo , Ludwig Christina , Felix Georg , Seidl Michael F. , Becker Annette , Nürnberger Thorsten , Hahn Matthias , Gust Bertolt , Gross Harald , Hückelhoven Ralph , Gust Andrea A. 
Published: June 2023

AbstractThe Arabidopsis thaliana Receptor-Like Protein RLP30 contributes to immunity against the fungal pathogen Sclerotinia sclerotiorum. Here we identify the RLP30-ligand as a small cysteine-rich protein (SCP) that occurs in many fungi and oomycetes and is also recognized by the Nicotiana benthamiana RLP RE02. However, RLP30 and RE02 share little sequence similarity and respond to different parts of the native/folded protein. Moreover, some Brassicaceae other than Arabidopsis also respond to a linear SCP peptide instead of the folded protein, suggesting that SCP is an eminent immune target that led to the convergent evolution of distinct immune receptors in plants. Surprisingly, RLP30 shows a second ligand specificity for a SCP-nonhomologous protein secreted by bacterial Pseudomonads. RLP30 expression in N. tabacum results in quantitatively lower susceptibility to bacterial, fungal and oomycete pathogens, thus demonstrating that detection of immunogenic patterns by Arabidopsis RLP30 is involved in defense against pathogens from three microbial kingdoms.
Exceptionally high charge mobility in phthalocyanine-based poly(benzimidazobenzophenanthroline)-ladder-type two-dimensional conjugated polymers
Authors: Wang Mingchao , Fu Shuai , Petkov Petko , Fu Yubin , Zhang Zhitao , Liu Yannan , Ma Ji , Chen Guangbo , Gali Sai Manoj , Gao Lei , Lu Yang , Paasch Silvia , Zhong Haixia , Steinrück Hans-Peter , Cánovas Enrique , Brunner Eike , Beljonne David , Bonn Mischa , Wang Hai I. , Dong Renhao , Feng Xinliang 
Published: June 2023

AbstractTwo-dimensional conjugated polymers (2DCPs), composed of multiple strands of linear conjugated polymers with extended in-plane π-conjugation, are emerging crystalline semiconducting polymers for organic (opto)electronics. They are represented by two-dimensional π-conjugated covalent organic frameworks, which typically suffer from poor π-conjugation and thus low charge carrier mobilities. Here we overcome this limitation by demonstrating two semiconducting phthalocyanine-based poly(benzimidazobenzophenanthroline)-ladder-type 2DCPs (2DCP-MPc, with M = Cu or Ni), which are constructed from octaaminophthalocyaninato metal(ii) and naphthalenetetracarboxylic dianhydride by polycondensation under solvothermal conditions. The 2DCP-MPcs exhibit optical bandgaps of ~1.3 eV with highly delocalized π-electrons. Density functional theory calculations unveil strongly dispersive energy bands with small electron–hole reduced effective masses of ~0.15m0 for the layer-stacked 2DCP-MPcs. Terahertz spectroscopy reveals the band transport of Drude-type free carriers in 2DCP-MPcs with exceptionally high sum mobility of electrons and holes of ~970 cm2 V−1 s−1 at room temperature, surpassing that of the reported linear conjugated polymers and 2DCPs. This work highlights the critical role of effective conjugation in enhancing the charge transport properties of 2DCPs and the great potential of high-mobility 2DCPs for future (opto)electronics.
Transcriptomic classes of BCR-ABL1 lymphoblastic leukemia
Authors: Kim Jaeseung C. , Chan-Seng-Yue Michelle , Ge Sabrina , Zeng Andy G. X. , Ng Karen , Gan Olga I. , Garcia-Prat Laura , Flores-Figueroa Eugenia , Woo Tristan , Zhang Amy Xin Wei , Arruda Andrea , Chithambaram Shivapriya , Dobson Stephanie M. , Khoo Amanda , Khan Shahbaz , Ibrahimova Narmin , George Ann , Tierens Anne , Hitzler Johann , Kislinger Thomas , Dick John E. , McPherson John D. , Minden Mark D. , Notta Faiyaz 
Published: June 2023

AbstractIn BCR-ABL1 lymphoblastic leukemia, treatment heterogeneity to tyrosine kinase inhibitors (TKIs), especially in the absence of kinase domain mutations in BCR-ABL1, is poorly understood. Through deep molecular profiling, we uncovered three transcriptomic subtypes of BCR-ABL1 lymphoblastic leukemia, each representing a maturation arrest at a stage of B-cell progenitor differentiation. An earlier arrest was associated with lineage promiscuity, treatment refractoriness and poor patient outcomes. A later arrest was associated with lineage fidelity, durable leukemia remissions and improved patient outcomes. Each maturation arrest was marked by specific genomic events that control different transition points in B-cell development. Interestingly, these events were absent in BCR-ABL1+ preleukemic stem cells isolated from patients regardless of subtype, which supports that transcriptomic phenotypes are determined downstream of the leukemia-initialing event. Overall, our data indicate that treatment response and TKI efficacy are unexpected outcomes of the differentiation stage at which this leukemia transforms.
Lactation-associated macrophages exist in murine mammary tissue and human milk
Authors: Cansever Dilay , Petrova Ekaterina , Krishnarajah Sinduya , Mussak Caroline , Welsh Christina A. , Mildenberger Wiebke , Mulder Kevin , Kreiner Victor , Roussel Elsa , Stifter Sebastian A. , Andreadou Myrto , Zwicky Pascale , Jurado Nicole Puertas , Rehrauer Hubert , Tan Ge , Liu Zhaoyuan , Blériot Camille , Ronchi Francesca , Macpherson Andrew J. , Ginhoux Florent , Natalucci Giancarlo , Becher Burkhard , Greter Melanie 
Published: June 2023

AbstractMacrophages are involved in immune defense, organogenesis and tissue homeostasis. Macrophages contribute to the different phases of mammary gland remodeling during development, pregnancy and involution postlactation. Less is known about the dynamics of mammary gland macrophages in the lactation stage. Here, we describe a macrophage population present during lactation in mice. By multiparameter flow cytometry and single-cell RNA sequencing, we identified a lactation-induced CD11c+CX3CR1+Dectin-1+ macrophage population (liMac) that was distinct from the two resident F4/80hi and F4/80lo macrophage subsets present pregestationally. LiMacs were predominantly monocyte-derived and expanded by proliferation in situ concomitant with nursing. LiMacs developed independently of IL-34, but required CSF-1 signaling and were partly microbiota-dependent. Locally, they resided adjacent to the basal cells of the alveoli and extravasated into the milk. We found several macrophage subsets in human milk that resembled liMacs. Collectively, these findings reveal the emergence of unique macrophages in the mammary gland and milk during lactation.
Delineation of partial melts and crustal heterogeneities within the crust beneath Kumaon Himalaya, India from Lg wave attenuation
Authors: Parija Mahesh Prasad , Kumar Sudesh , V H Arjun 
Published: June 2023

AbstractThe crustal seismic attenuation or the Q structure is studied by using the Fourier spectra of Lg-wave along the Tanakpur- Dharchula- Dharma transect in the Kumaon Himalaya. The 1 Hz Lg Q (Q0) values are computed between different pairs of two stations and the observed values are later utilized to calculate the lateral variation in the Q0 values by following a back projection algorithm. This computation of Q0 values utilizes five regional distance earthquakes having moment magnitude (Mw) ≥ 4.0, which lie along the great circle path of the transect. Three of the five earthquakes occurred in the Tibetan plateau and the and the others occurred to the southwest on the Indian shield and are well recorded at all the 32 broadband seismographs operated between September 2018 and March 2022. The estimate Qo values range from 63 ± 2 and 203 ± 25, with the lowest value in the Lesser Himalaya and the highest across part of the Indo Gangetic Plain and Siwalik Himalaya. The Q0 model has low values ∼200 along the profile in the Indo Gangetic Plain and the Siwalik Himalaya, and are correlated with 2–5 km thick sedimentary layers below the Himalaya and the adjoining Indo-Gangetic Plain. We observe two distinctly different Q0 values to the northeast in the Lesser Himalaya tectonic unit. The region lying between the South Almora Thrust (SAT) and the Berinag Thrust (BT) shows extremely low Q0 values (∼60) but increases further north towards the Vaikrita Thrust (VT) to ∼200. The possible explanation for observing such huge variation of the Q0 values within a single tectonic unit may be the presence of fluid rich ramp structures, which introduces crustal heterogeneities and traps the aqueous fluids or partial melts lying within the crust. The Lg Q0 values decrease to the North and become ∼166 for station pairs in the Higher Himalaya and Tethys Himalaya tectonic units. The low Q0 values observed in this region may be correlated with low viscous partial melts in the form of Miocene leucogranite plutons, which resulted out of the Indo-Asian collision. The attenuation structure along the profile in the Kumaon Himalaya can be used to estimate ground motions of future earthquakes in the area and can contribute to seismic hazard assessment in the Himalaya and neighbouring regions.
Machine learning algorithms for predicting days of high incidence for out-of-hospital cardiac arrest
Authors: Shimada-Sammori Kaoru , Shimada Tadanaga , Miura Rie E. , Kawaguchi Rui , Yamao Yasuo , Oshima Taku , Oami Takehiko , Tomita Keisuke , Shinozaki Koichiro , Nakada Taka-aki 
Published: June 2023

AbstractPredicting out-of-hospital cardiac arrest (OHCA) events might improve outcomes of OHCA patients. We hypothesized that machine learning algorithms using meteorological information would predict OHCA incidences. We used the Japanese population-based repository database of OHCA and weather information. The Tokyo data (2005–2012) was used as the training cohort and datasets of the top six populated prefectures (2013–2015) as the test. Eight various algorithms were evaluated to predict the high-incidence OHCA days, defined as the daily events exceeding 75% tile of our dataset, using meteorological and chronological values: temperature, humidity, air pressure, months, days, national holidays, the day before the holidays, the day after the holidays, and New Year’s holidays. Additionally, we evaluated the contribution of each feature by Shapley Additive exPlanations (SHAP) values. The training cohort included 96,597 OHCA patients. The eXtreme Gradient Boosting (XGBoost) had the highest area under the receiver operating curve (AUROC) of 0.906 (95% confidence interval; 0.868–0.944). In the test cohorts, the XGBoost algorithms also had high AUROC (0.862–0.923). The SHAP values indicated that the “mean temperature on the previous day” impacted the most on the model. Algorithms using machine learning with meteorological and chronological information could predict OHCA events accurately.
Middle-shallow feature aggregation in multimodality for face anti-spoofing
Authors: Li Chunyan , Li Zhiyong , Sun Jianhong , Li Rui 
Published: June 2023

AbstractAt present, most advanced algorithms for face anti-spoofing use stacked convolutions and residual structure to obtain complex characteristics of deep networks, and then distinguish liveness and deception. These methods ignore the shallow features that contain more detailed information. As a result, the model lacks sufficient fine-grained information, which affects the accuracy and robustness of the algorithm. In this paper, we use the simple features of the shallow network to increase the fine-grained information of the model, so as to improve the performance of the algorithm. First of all, the shallow features are spliced to the middle layer by "shortcut" structure to reserve more details for the middle layer features and improve their detail representation ability. Secondly, the network is initialized with the best pre-trained model parameters under unbalanced samples, and then trained on the balanced samples to improve the classification ability of the model. Finally, RS Block based on depthwise separable convolution is used to replace res module, and model parameters and floating point operations are reduced from 18G and 61 M to 1.9 M and 347 M. The algorithm is simulated on CASIA-SURF dataset, and the results show that the average classification error rate (ACER) is only 0.0008, TPR@FPR = 10E−4 reaches 0.9990, which is better than the previous face anti deception methods.
A comparison of machine learning methods to classify radioactive elements using prompt-gamma-ray neutron activation data
Authors: Mathew Jino , Kshirsagar Rohit , Abidin Dzariff Z. , Griffin James , Kanarachos Stratis , James Jithin , Alamaniotis Miltiadis , Fitzpatrick Michael E. 
Published: June 2023

AbstractThe detection of illicit radiological materials is critical to establishing a robust second line of defence in nuclear security. Neutron-capture prompt-gamma activation analysis (PGAA) can be used to detect multiple radioactive materials across the entire Periodic Table. However, long detection times and a high rate of false positives pose a significant hindrance in the deployment of PGAA-based systems to identify the presence of illicit substances in nuclear forensics. In the present work, six different machine-learning algorithms were developed to classify radioactive elements based on the PGAA energy spectra. The model performance was evaluated using standard classification metrics and trend curves with an emphasis on comparing the effectiveness of algorithms that are best suited for classifying imbalanced datasets. We analyse the classification performance based on Precision, Recall, F1-score, Specificity, Confusion matrix, ROC-AUC curves, and Geometric Mean Score (GMS) measures. The tree-based algorithms (Decision Trees, Random Forest and AdaBoost) have consistently outperformed Support Vector Machine and K-Nearest Neighbours. Based on the results presented, AdaBoost is the preferred classifier to analyse data containing PGAA spectral information due to the high recall and minimal false negatives reported in the minority class.
Malaria surveillance, outbreak investigation, response and its determinant factors in Waghemra Zone, Northeast Ethiopia: unmatched case–control study
Authors: Debash Habtu , Nigatie Marye , Bisetegn Habtye , Feleke Daniel Getacher , Tesfaw Gebru , Amha Askale , Abate Megbaru Alemu , Gedefie Alemu 
Published: June 2023

AbstractMalaria is a major global public health concern, with around half of the world's population at risk of infection. It is one of the most common epidemic-prone diseases, resulting in on-going epidemics and significant public health problems. On September 12, 2022, Waghemra Zone malaria monitoring data revealed that the district was suffering an unusually high number of malaria cases. Therefore, the aim of this study was to assess the occurrence of malaria outbreaks and investigate contracting factors in Waghemra Zone, Northeast Ethiopia. A community-based case–control study with a 1:1 ratio was employed at Waghemra Zone from September 14 to November 27, 2022. A total of 260 individuals (130 cases and 130 controls) were included in the study. A structured questionnaire was used to collect the data. Malaria cases were confirmed by either microscopy or malaria rapid diagnostic tests. The magnitude of the outbreak was described by place, person, and time. A multivariable logistic regression analysis was conducted to identify malaria risk factors. A total of 13,136 confirmed cases of malaria were detected in the Waghemra zone, with an overall attack rate of 26.5 per 1000 and slide positivity rate was 43.0%. The predominant species was Plasmodium falciparum accounting for 66.1%. Children under five years old (AOR = 5.1; 95% CI 2.6–23.0), the presence of artificial water-holding bodies (AOR: 2.7; 95% CI 1.340–5.420), intermittent rivers closer to the living house (AOR = 4.9; 95% CI 2.51–9.62), sleeping outside a home (AOR = 4.9; 95% CI 2.51–9.62), and a lack of knowledge about malaria transmission and prevention (AOR: 9.7; 95% CI 4.459–20.930) were factors associated with malaria contraction. The overall attack rate for malaria during this outbreak was high. Children less than five years, the presence of mosquito breeding sites, staying outdoors overnight, and a lack of knowledge on malaria transmission and prevention were predictors of malaria. Early management of local vector breeding places, as well as adequate health education on malaria transmission and prevention methods, should be provided to the community to prevent such outbreaks in the future.
Responses of yield, quality and water use efficiency of potato grown under different drip irrigation and nitrogen levels
Authors: Akkamis Mustafa , Caliskan Sevgi 
Published: June 2023

AbstractProper irrigation and fertilization are essential for achieve high tuber yield and quality in potato production. However, the high cost of these inputs necessitate optimization of their use to improve both water use efficiency and crop productivity. This study aimed to investigate the impact of irrigation and nitrogen fertilization on potato yield, quality and water use efficiency. The research included different drip irrigation treatments (100%, 66%, and 33% of field capacity) and nitrogen levels: 0 (N0), 100 (N1), 200 (N2), 300 (N3), 400 (N4) and 500 (N5) kg N ha−1. The results indicated that potato yield and growth were more sensitive to irrigation treatment than nitrogen levels. Full irrigation with 300 kg N ha−1 produced the highest total tuber yield, while low irrigation treatments resulted in significantly lower yields. In contrast, the 66% field capacity irrigation treatment consistently had the highest water use efficiency in both years of the study. Furthermore, the study showed that the quality characteristics of the tubers were negatively impacted by full irrigation treatments compared to low irrigation. These findings suggest that with appropriate irrigation and nitrogen application, potatoes can be produced with acceptable yields while conserving water and minimizing nitrogen use. This research emphasizes the importance of optimizing inputs to improve water use efficiency and yield productivity while reducing water. As a result, obtaining useful information on crop management for farmers to make informed decisions may be possible by achieving optimal irrigation and nitrogen levels.
Comparison of automated quantification of amyloid deposition between PMOD and Heuron
Authors: Roh Hyun Woong , Son Sang Joon , Hong Chang Hyung , Moon So Young , Lee Sun Min , Seo Sang Won , Choi Seong Hye , Kim Eun-Joo , Cho Soo Hyun , Kim Byeong Chae , Park Seongbeom , Song Soohwa , An Young-Sil 
Published: June 2023

AbstractSeveral programs are widely used for clinical and research purposes to automatically quantify the degree of amyloid deposition in the brain using positron emission tomography (PET) images. Given that very few studies have investigated the use of Heuron, a PET image quantification software approved for clinical use, this study aimed to compare amyloid deposition values quantified from 18F-flutemetamol PET images using PMOD and Heuron. Amyloid PET data obtained from 408 patients were analysed using each quantitative program; moreover, the standardized uptake value ratios (SUVRs) of target areas were obtained by dividing the standardized uptake value (SUV) of the target region by the SUV of cerebellar grey matter as a reference. Compared with PMOD, Heuron yielded significantly higher SUVRs for all target areas (paired sample t-test, p < 0.001), except for the PC/PCC (p = 0.986). However, the Bland–Altman plot analysis indicated that the two quantitative methods may be used interchangeably. Moreover, receiver operating characteristic curve analysis revealed no significant between-method difference in the performance of the SUVRs in evaluating the visual positivity of amyloid deposits (p = 0.948). In conclusion, Heuron and PMOD have comparable performance in quantifying the degree of amyloid deposits in PET images.
The effects of propolis on pro-oxidant–antioxidant balance, glycemic control, and quality of life in chronic kidney disease: a randomized, double-blind, placebo-controlled trial
Authors: Anvarifard Paniz , Ostadrahimi Alireza , Ardalan Mohammadreza , Anbari Maryam , Ghoreishi Zohreh 
Published: June 2023

AbstractChronic kidney disease (CKD) is a progressive kidney damage with an increasing prevalence. Some evidence suggests that propolis as a novel antioxidant, anti-inflammatory, and immunomodulatory agent may have beneficial effects in CKD. The aim of this study was to evaluate the efficacy of propolis on some kidney function parameters, pro-oxidant–antioxidant balance (PAB), glycemic status, quality of life, and blood pressure (BP) in patients with CKD. In this study, 44 patients with CKD were randomly assigned to receive propolis capsules at a dose of 250 mg daily or placebo for three months. Of 44 randomized individuals, 35 completed the trial. At the end of the intervention (end of month three), improvement in some dimensions of health-related quality of life (HRQoL) (derived from Kidney Disease and Quality of Life Short-Form (KDQOL-$${\mathrm{SF}}^{\mathrm{TM}}$$

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, v. 1.3) questionnaire) were significantly higher in the propolis group than the placebo group, even after adjustment for baseline values, present of diabetes, and age (P < 0.05). Like systolic and diastolic BP, changes in serum creatinine, 24-h urine volume and protein, fasting blood sugar (FBS), hemoglobin A1C (HbA1C), insulin, homeostasis model of assessment-insulin resistance (HOMA-IR), quantitative insulin sensitivity check index (QUICKI), and PAB did not differ significantly between the two groups (P > 0.05). No serious adverse events were reported throughout the study. Propolis supplementation may improve the HRQoL of CKD patients. More studies are needed to validate the adjunct use of propolis for metabolic control of CKD patients.
Microplastics in snow from protected areas in Hokkaido, the northern island of Japan
Authors: Ohno Hiroshi , Iizuka Yoshinori 
Published: June 2023

AbstractSnowfall is regarded as a carrier of airborne microplastics (MPs). Deposited snow can function as a temporary reservoir for atmospheric MPs. Nevertheless, knowledge and understanding of MPs in snow remain sparse. This study investigates the abundance, composition, size (> 30 µm), and shape of MPs in snow specimens from various nature preservation areas and also from urban sites in Hokkaido. Various polymeric-type MPs with mostly fragmentary shapes were detected among the specimens. More than half of MPs were in the smallest size class (30–60 µm), implying the presence of more MPs below the limit (< 30 µm). Concentrations of MPs ranged from 1.5 × 102 to 4.2 × 103 particles/L. The results demonstrated that microplastic abundance generally decreases concomitantly with increasing remoteness of sampling sites. Observed features of MPs at different locations and their relation to geographical settings have indicated that the ubiquitously observed fine particles (mainly alkyd, ethylene–vinyl acetate, and polyethylene) are attributable to long-distance atmospheric transportation, whereas the rubber and larger particles especially found near highways and cities are from local sources of plastic. Taken together, these findings suggest important implications for elucidating the nature and distribution of atmospheric MPs.