bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning
Authors: Abrol Anees , Fu Zening , Salman Mustafa , Silva Rogers , Du Yuhui , Plis Sergey , Calhoun Vince 
Published: January 2021

AbstractRecent critical commentaries unfavorably compare deep learning (DL) with standard machine learning (SML) approaches for brain imaging data analysis. However, their conclusions are often based on pre-engineered features depriving DL of its main advantage — representation learning. We conduct a large-scale systematic comparison profiled in multiple classification and regression tasks on structural MRI images and show the importance of representation learning for DL. Results show that if trained following prevalent DL practices, DL methods have the potential to scale particularly well and substantially improve compared to SML methods, while also presenting a lower asymptotic complexity in relative computational time, despite being more complex. We also demonstrate that DL embeddings span comprehensible task-specific projection spectra and that DL consistently localizes task-discriminative brain biomarkers. Our findings highlight the presence of nonlinearities in neuroimaging data that DL can exploit to generate superior task-discriminative representations for characterizing the human brain.
Evaluation of microalgae polysaccharides as biostimulants of tomato plant defense using metabolomics and biochemical approaches
Authors: Rachidi Farid , Benhima Redouane , Kasmi Yassine , Sbabou Laila , Arroussi Hicham El 
Published: January 2021

AbstractMicroalgal polysaccharides (PSs) may be an effective elicitor agent that can efficiently protect plants against biotic stresses. In this study, wee investigates, the effect of PS obtained from microalgae and cyanobacteria (D. salina MS002, P. tricorontum MS023, Porphyridium sp. MS081, Desmodesmus sp., D. salina MS067 and A. platensis MS001) on the biochemical and metabolomics markers linked to defense pathways in tomato plants. The phenylalanine ammonia lyase (PAL), chitinase, 1,3-beta-glucanase and peroxidase (POX) activities have been improved in tomato plants leaves treated by polysaccharides extracted from P. triocnutum (238.26%); Desmodesmus sp. (19.95%); P. triocnutum (137.50%) and Porphyridium sp. (47.28%) respectively. For proteins, polyphenols and H2O2, the maximum effect was induced by D. salina 067 (55.01%), Porphyridium sp. (3.97%) and A. platensis (35.08%) respectively. On the other hand, Gas Chromatography-mass spectrometry (GC–MS) metabolomics analysis showed that PSs induced the modification of metabolite profile involved in the wax construction of tomato leaves, such as fatty acids, alkanes, alkenes and phytosterol. PS treatments improved the accumulation of fatty acids C16:3, C18:2 and C18:3 released from the membrane lipids as precursors of oxylipin biosynthesis which are signaling molecules of plant defense. In addition, PS treatment induced the accumulation of C18:0 and Azelaic acid which is a regulator of salicylic acid-dependent systemic acquired resistance. However, molecular and metabolic studies can determine more precisely the mode of action of microalgal polysaccharides as biostimulants/elicitors plant defense.
1H-NMR metabolomics reveals a multitarget action of Crithmum maritimum ethyl acetate extract in inhibiting hepatocellular carcinoma cell growth
Authors: Gnocchi Davide , Del Coco Laura , Girelli Chiara Roberta , Castellaneta Francesca , Cesari Gianluigi , Sabbà Carlo , Fanizzi Francesco Paolo , Mazzocca Antonio 
Published: January 2021

AbstractHepatocellular carcinoma (HCC) is nowadays the sixth cause of tumour-related deceases worldwide, estimated to become the third in Western countries by 2030. New drugs for HCC treatment still have many adverse effects. Several lines of evidence indicate that plant metabolites offer concrete opportunities for developing new therapeutic strategies for many diseases, including cancer. We previously reported that ethyl acetate extract of a spontaneous edible plant harvested in Apulia, Crithmum maritimum, significantly inhibited cell growth in HCC cells. By 1H-NMR spectroscopy, here we show that Crithmum maritimum ethyl acetate extract counteracts the Warburg effect, by reducing intracellular lactate, inhibits protein anabolism, by decreasing amino acid level, and affects membrane biosynthesis by lowering choline and phosphocholine. Also, we observed an effect on lipid homeostasis, with a reduction in triglycerides, cholesterol, monounsaturated fatty acids (MUFA), and diunsaturated fatty acids (DUFA), and an increase in polyunsaturated fatty acids (PUFA). Taken together, these data demonstrate that Crithmum maritimum-induced cytostasis is exerted through a multi-effect action, targeting key metabolic processes in HCC cells. Overall, our findings highlight the role of Crithmum maritimum as a promising tool for the prevention and the improvement of the therapeutic options for HCC and other types of tumours.
An absorbance method for analysis of enzymatic degradation kinetics of poly(ethylene terephthalate) films
Authors: Zhong-Johnson En Ze Linda , Voigt Christopher A. , Sinskey Anthony J. 
Published: January 2021

AbstractIncreased interest in poly(ethylene terephthalate) (PET)-degrading enzymes (PETases) have generated efforts to find mutants with improved catalytic activity and thermostability. Here, we present a simple and fast method to determine relative enzyme kinetics through bulk absorbance measurements of released products over time. A thermostable variant of PETase from Ideonella sakaiensis was engineered (R280A S121E D186H N233C S282C) with a denaturation temperature of 69.4 ± 0.3 °C. This was used to assess the method’s ability to determine relative enzyme kinetics across variants and reveal structure–function relationships. Measurements at 24 and 72 h at 400 nM of enzyme suggest that the mutations improved catalytic rates 5- to 7-fold. On the contrary, kinetic analyses of the thermostable variant and wild-type reveal different reaction trajectories despite similar maximum catalytic rates, resulting in higher product accumulation from the thermostable variant over time. The results of the assay support the necessity for kinetic measurements to determine relationships between sequence and function for IsPETase and other PET hydrolases.
Leishmania donovani infection suppresses Allograft Inflammatory Factor-1 in monocytes and macrophages to inhibit inflammatory responses
Authors: da Silva Ricardo Louzada , Elizondo Diana M. , Brandy Nailah Z. D. , Haddock Naomi L. , Boddie Thomas A. , de Oliveira Laís Lima , de Jesus Amélia Ribeiro , de Almeida Roque Pacheco , de Moura Tatiana Rodrigues , Lipscomb Michael W. 
Published: January 2021

AbstractMacrophages and monocytes are important for clearance ofLeishmaniainfections. However, immune evasion tactics employed by the parasite results in suppressed inflammatory responses, marked by deficient macrophage functions and increased accumulation of monocytes. This results in an ineffective ability to clear parasite loads. Allograft Inflammatory Factor-1 (AIF1) is expressed in myeloid cells and serves to promote immune responses. However, AIF1 involvement in monocyte and macrophage functions during parasitic infections has not been explored. This study now shows thatLeishmania donovaniinhibits AIF1 expression in macrophages to block pro-inflammatory responses. Mice challenged with the parasite had markedly reduced AIF1 expression in splenic macrophages. Follow-up studies using in vitro approaches confirmed thatL. donovaniinfection in macrophages suppresses AIF1 expression, which correlated with reduction in pro-inflammatory cytokine production and increased parasite load. Ectopic overexpression of AIF1 in macrophages provided protection from infection, marked by robust pro-inflammatory cytokine production and efficient pathogen clearance. Further investigations found that inhibiting AIF1 expression in bone marrow cells or monocytes impaired differentiation into functional macrophages. Collectively, results show that AIF1 is a critical regulatory component governing monocyte and macrophage immune functions and thatL. donovaniinfection can suppress the gene as an immune evasion tactic.
Fine scale human genetic structure in three regions of Cameroon reveals episodic diversifying selection
Authors: Esoh Kevin K. , Apinjoh Tobias O. , Nyanjom Steven G. , Wonkam Ambroise , Chimusa Emile R. , Amenga-Etego Lucas , Amambua-Ngwa Alfred , Achidi Eric A. 
Published: January 2021

AbstractInferences from genetic association studies rely largely on the definition and description of the underlying populations that highlight their genetic similarities and differences. The clustering of human populations into subgroups (population structure) can significantly confound disease associations. This study investigated the fine-scale genetic structure within Cameroon that may underlie disparities observed with Cameroonian ethnicities in malaria genome-wide association studies in sub-Saharan Africa. Genotype data of 1073 individuals from three regions and three ethnic groups in Cameroon were analyzed using measures of genetic proximity to ascertain fine-scale genetic structure. Model-based clustering revealed distinct ancestral proportions among the Bantu, Semi-Bantu and Foulbe ethnic groups, while haplotype-based coancestry estimation revealed possible longstanding and ongoing sympatric differentiation among individuals of the Foulbe ethnic group, and their Bantu and Semi-Bantu counterparts. A genome scan found strong selection signatures in the HLA gene region, confirming longstanding knowledge of natural selection on this genomic region in African populations following immense disease pressure. Signatures of selection were also observed in theHBBgene cluster, a genomic region known to be under strong balancing selection in sub-Saharan Africa due to its co-evolution with malaria. This study further supports the role of evolution in shaping genomes of Cameroonian populations and reveals fine-scale hierarchical structure among and within Cameroonian ethnicities that may impact genetic association studies in the country.
Vulnerability to watershed erosion and coastal deposition in the tropics
Authors: Browning Trevor N. , Sawyer Derek E. 
Published: January 2021

AbstractOver half of the global population is projected to live in the tropics by 2050. Sustainable land development will be challenged by enhanced sediment erosion and deposition, which can negatively impact water quality and ecosystem services in inland and coastal waterways. Existing erosion assessments treat watersheds and coastal zones separately, but we connect them in a two-part vulnerability index to watershed erosion and coastal deposition at 0.0004° (~ 45 m) resolution throughout the tropics. We use open-source datasets and a simple, GIS-based method geared toward tropical, novice end-users. Part 1 of the index reveals a majority of the tropics is vulnerable to erosion. Vulnerability is highest where there are co-occurrences of earthquakes, steep slopes, and high precipitation such as the Caribbean and Southeast Asia. In Part 2, we assess erosion vulnerability at 4 watersheds and include their coastal systems, which can enhance or diminish vulnerability of the entire system to coastal deposition.
The corticolimbic structural covariance network as an early predictive biosignature for cognitive impairment in Parkinson's disease
Authors: Chen Yueh-Sheng , Chen Hsiu-Ling , Lu Cheng-Hsien , Lee Chih-Ying , Chou Kun-Hsien , Chen Meng-Hsiang , Yu Chiun-Chieh , Lai Yun-Ru , Chiang Pi-Ling , Lin Wei-Che 
Published: January 2021

AbstractStructural covariance assesses similarities in gray matter between brain regions and can be applied to study networks of the brain. In this study, we explored correlations between structural covariance networks (SCNs) and cognitive impairment in Parkinson’s disease patients. 101 PD patients and 58 age- and sex-matched healthy controls were enrolled in the study. For each participant, comprehensive neuropsychological testing using the Wechsler Adult Intelligence Scale-III and Cognitive Ability Screening Instrument were conducted. Structural brain MR images were acquired using a 3.0T whole body GE Signa MRI system. T1 structural images were preprocessed and analyzed using Statistical Parametric Mapping software (SPM12) running on Matlab R2016a for voxel-based morphometric analysis and SCN analysis. PD patients with normal cognition received follow-up neuropsychological testing at 1-year interval. Cognitive impairment in PD is associated with degeneration of the amygdala/hippocampus SCN. PD patients with dementia exhibited increased covariance over the prefrontal cortex compared to PD patients with normal cognition (PDN). PDN patients who had developed cognitive impairment at follow-up exhibited decreased gray matter volume of the amygdala/hippocampus SCN in the initial MRI. Our results support a neural network-based mechanism for cognitive impairment in PD patients. SCN analysis may reveal vulnerable networks that can be used to early predict cognitive decline in PD patients.
FlavorGraph: a large-scale food-chemical graph for generating food representations and recommending food pairings
Authors: Park Donghyeon , Kim Keonwoo , Kim Seoyoon , Spranger Michael , Kang Jaewoo 
Published: January 2021

AbstractFood pairing has not yet been fully pioneered, despite our everyday experience with food and the large amount of food data available on the web. The complementary food pairings discovered thus far created by the intuition of talented chefs, not by scientific knowledge or statistical learning. We introduce FlavorGraph which is a large-scale food graph by relations extracted from million food recipes and information of 1,561 flavor molecules from food databases. We analyze the chemical and statistical relations of FlavorGraph and apply our graph embedding method to better represent foods in dense vectors. Our graph embedding method is a modification of metapath2vec with an additional chemical property learning layer and quantitatively outperforms other baseline methods in food clustering. Food pairing suggestions made based on the food representations of FlavorGraph help achieve better results than previous works, and the suggestions can also be used to predict relations between compounds and foods. Our research offers a new perspective on not only food pairing techniques but also food science in general.
Delineation of the electrocardiogram with a mixed-quality-annotations dataset using convolutional neural networks
Authors: Jimenez-Perez Guillermo , Alcaine Alejandro , Camara Oscar 
Published: January 2021

AbstractDetection and delineation are key steps for retrieving and structuring information of the electrocardiogram (ECG), being thus crucial for numerous tasks in clinical practice. Digital signal processing (DSP) algorithms are often considered state-of-the-art for this purpose but require laborious rule readaptation for adapting to unseen morphologies. This work explores the adaptation of the the U-Net, a deep learning (DL) network employed for image segmentation, to electrocardiographic data. The model was trained using PhysioNet’s QT database, a small dataset of 105 2-lead ambulatory recordings, while being independently tested for many architectural variations, comprising changes in the model’s capacity (depth, width) and inference strategy (single- and multi-lead) in a fivefold cross-validation manner. This work features several regularization techniques to alleviate data scarcity, such as semi-supervised pre-training with low-quality data labels, performing ECG-based data augmentation and applying in-built model regularizers. The best performing configuration reached precisions of 90.12%, 99.14% and 98.25% and recalls of 98.73%, 99.94% and 99.88% for the P, QRS and T waves, respectively, on par with DSP-based approaches. Despite being a data-hungry technique trained on a small dataset, a U-Net based approach demonstrates to be a viable alternative for this task.
Linking plant and soil indices for water stress management in black gram
Authors: Khorsand Afshin , Rezaverdinejad Vahid , Asgarzadeh Hossein , Majnooni-Heris Abolfazl , Rahimi Amir , Besharat Sina , Sadraddini Ali Ashraf 
Published: January 2021

AbstractMeasurement of plant and soil indices as well as their combinations are generally used for irrigation scheduling and water stress management of crops and horticulture. Rapid and accurate determination of irrigation time is one of the most important issues of sustainable water management in order to prevent plant water stress. The objectives of this study are to develop baselines and provide irrigation scheduling relationships during different stages of black gram growth, determine the critical limits of plant and soil indices, and also determine the relationships between plant physiology and soil indices. This study was conducted in a randomized complete block design at the four irrigation levels 50 (I1), 75 (I2), 100 (I3 or non-stress treatment) and 125 (I4) percent of crop’s water requirement with three replications in Urmia region in Iran in order to irrigation scheduling of black gram using indices such as canopy temperature (Tc), crop water stress index (CWSI), relative water content (RWC), leaf water potential (LWP), soil water (SW) and penetration resistance (Q) of soil under one-row drip irrigation. The plant irrigation scheduling was performed by using the experimental crop water stress index (CWSI) method. The upper and lower baseline equations as well as CWSI were calculated for the three treatments of I1, I2 and I3 during the plant growth period. Using the extracted baselines, the mean CWSI values for the three treatments of I1, I2 and I3 were calculated to be 0.37, 0.23 and 0.15, respectively, during the growth season. Finally, using CWSI, the necessary equations were provided to determine the irrigation schedule for the four growing stages of black gram, i.e. floral induction-flowering, pod formation, seed and pod filling and physiological maturity, as (Tc − Ta)c = 1.9498 − 0.1579(AVPD), (Tc − Ta)c = 4.4395 − 0.1585(AVPD), (Tc − Ta)c = 2.4676 − 0.0578(AVPD) and (Tc − Ta)c = 5.7532 − 0.1462(AVPD), respectively. In this study, soil and crop indices, which were measured simultaneously at maximum stress time, were used as a complementary index to remove CWSI constraints. It should be noted that in Urmia, the critical difference between the canopy temperature and air temperature (Tc − Ta), soil penetration resistance (Q), soil water (SW) and relative water content (RWC) for the whole growth period of black gram were − 0.036 °C, 10.43 MPa and 0.14 cm3 cm−3 and 0.76, respectively. Ideal point error (IPE) was also used to estimate RWC, (Tc − Ta) and LWP as well as to select the best regression model. According to the results, black gram would reduce its RWC less through reducing its transpiration and water management. Therefore, it can be used as a low-water-consuming crop. Furthermore, in light of available facilities, the farmer can use the regression equations between the obtained soil and plant indices and the critical boundaries for the irrigation scheduling of the field.
Crystal structure and DNA cleavage mechanism of the restriction DNA glycosylase R.CcoLI from Campylobacter coli
Authors: Miyazono Ken-ichi , Wang Delong , Ito Tomoko , Tanokura Masaru 
Published: January 2021

AbstractWhile most restriction enzymes catalyze the hydrolysis of phosphodiester bonds at specific nucleotide sequences in DNA, restriction enzymes of the HALFPIPE superfamily cleave N-glycosidic bonds, similar to DNA glycosylases. Apurinic/apyrimidinic (AP) sites generated by HALFPIPE superfamily proteins are cleaved by their inherent AP lyase activities, other AP endonuclease activities or heat-promoted β-elimination. Although the HALFPIPE superfamily protein R.PabI, obtained from a hyperthermophilic archaea, Pyrococcus abyssi, shows weak AP lyase activity, HALFPIPE superfamily proteins in mesophiles, such as R.CcoLI from Campylobacter coli and R. HpyAXII from Helicobacter pylori, show significant AP lyase activities. To identify the structural basis for the AP lyase activity of R.CcoLI, we determined the structure of R.CcoLI by X-ray crystallography. The structure of R.CcoLI, obtained at 2.35-Å resolution, shows that a conserved lysine residue (Lys71), which is stabilized by a characteristic β-sheet structure of R.CcoLI, protrudes into the active site. The results of mutational assays indicate that Lys71 is important for the AP lyase activity of R.CcoLI. Our results help to elucidate the mechanism by which HALFPIPE superfamily proteins from mesophiles efficiently introduce double-strand breaks to specific sites on double-stranded DNA.
Histone acetyltransferase PfGCN5 regulates stress responsive and artemisinin resistance related genes in Plasmodium falciparum
Authors: Rawat Mukul , Kanyal Abhishek , Sahasrabudhe Aishwarya , Vembar Shruthi Sridhar , Lopez-Rubio Jose-Juan , Karmodiya Krishanpal 
Published: January 2021

AbstractPlasmodium falciparum has evolved resistance to almost all front-line drugs including artemisinin, which threatens malaria control and elimination strategies. Oxidative stress and protein damage responses have emerged as key players in the generation of artemisinin resistance. In this study, we show that PfGCN5, a histone acetyltransferase, binds to the stress-responsive genes in a poised state and regulates their expression under stress conditions. Furthermore, we show that upon artemisinin exposure, genome-wide binding sites for PfGCN5 are increased and it is directly associated with the genes implicated in artemisinin resistance generation like BiP and TRiC chaperone. Interestingly, expression of genes bound by PfGCN5 was found to be upregulated during stress conditions. Moreover, inhibition of PfGCN5 in artemisinin-resistant parasites increases the sensitivity of the parasites to artemisinin treatment indicating its role in drug resistance generation. Together, these findings elucidate the role of PfGCN5 as a global chromatin regulator of stress-responses with a potential role in modulating artemisinin drug resistance and identify PfGCN5 as an important target against artemisinin-resistant parasites.
A dyadic study of psychological well-being of individuals with Parkinson’s disease and their caregivers
Authors: Lee Yu , Chiou Yu-Jie , Hung Chi-Fa , Chang Yung-Yee , Chen Ying-Fa , Lin Tsu-Kung , Wang Liang-Jen 
Published: January 2021

AbstractParkinson's disease (PD) is an incapacitating neurodegenerative disease. Patients with PD and their caregivers may have interactive effects on each other’s psychological well-being. This study aimed to assess the dyadic dynamics of resilience, fatigue, and suicidal ideation on the depression severity of PD patients and their caregivers. In total, 175 PD patients and 175 caregivers were recruited at a medical center from August 2018 to May 2020. Structural equation modeling (SEM) was used to examine the actor/partner effects on the psychological well-being of both the PD patients and their caregivers. The most common psychiatric diagnoses of both the PD patients (28.6%) and their caregivers (11.4%) were depressive disorders. The PD patients’ and their caregivers’ fatigue, suicidal ideation, and lack of resilience were significantly associated with the severity of their depression, respectively. Interactive effects existed between psychological well-being of individuals with PD and their caregivers. Clinicians must be aware of, and manage, these contributing factors between PD patients and their caregivers in order to prevent them from worsening each other’s depression.