Miracle-dz/UniFAR-FTUs huggingface dataset:
Roles of the GA-mediated SPL Gene Family and miR156 in the Floral Development of Chinese Chestnut (Castanea mollissima)

Chestnut (Castanea mollissima) is a deciduous tree species with major economic and ecological value that is widely used in the study of floral development in woody plants due its monoecious and out-of-proportion characteristics. Squamosa promoter-binding protein-like (SPL) is a plant-specific transcription factor that plays an important role in floral development. In this study, a total of 18 SPL genes were identified in the chestnut genome, of which 10 SPL genes have complementary regions of CmmiR156. An analysis of the phylogenetic tree of the squamosa promoter-binding protein (SBP) domains of the SPL genes of Arabidopsis thaliana, Populus trichocarpa, and C. mollissima divided these SPL genes into eight groups. The evolutionary relationship between poplar and chestnut in the same group was similar. A structural analysis of the protein-coding regions (CDSs) showed that the domains have the main function of SBP domains and that other domains also play an important role in determining gene function. The expression patterns of CmmiR156 and CmSPLs in different floral organs of chestnut were analyzed by real-time quantitative PCR. Some CmSPLs with similar structural patterns showed similar expression patterns, indicating that the gene structures determine the synergy of the gene functions. The application of gibberellin (GA) and its inhibitor (Paclobutrazol, PP333) to chestnut trees revealed that these exert a significant effect on the number and length of the male and female chestnut flowers. GA treatment significantly increased CmmiR156 expression and thus significantly decreased the expression of its target gene, CmSPL6/CmSPL9/CmSPL16, during floral bud development. This finding indicates that GA might indirectly affect the expression of some of the SPL target genes through miR156. In addition, RNA ligase-mediated rapid amplification of the 5′ cDNA ends (RLM-RACE) experiments revealed that CmmiR156 cleaves CmSPL9 and CmSPL16 at the 10th and 12th bases of the complementary region. These results laid an important foundation for further study of the biological function of CmSPLs in the floral development of C. mollissima.
Atomic Simulations of Grain Structures and Deformation Behaviors in Nanocrystalline CoCrFeNiMn High-Entropy Alloy

Using the molecular dynamics method, the melting character, mechanical properties, microstructures, and strain deformation mechanisms of nanocrystalline CoCrFeNiMn high-entropy alloy are systematically investigated in the present work. The simulation results suggest that the melting point in CoCrFeNiMn high-entropy alloy decreases with the grain size, decreasing from 3.6 to 2.0 nm. The grain size has a significant effect on shear and Young’s modulus compared to bulk modulus. The stress-strain simulation demonstrates that the ultimate tensile strength decreases with the decrease of the grain size, while the plastic deformation increases with the decrease in grain size. While the average grain size decreases to 2.0 nm, the amorphization induced by small grain size reduces plastic deformation. The common neighbor analysis shows that the face-centered cubic (FCC) composition of CoCrFeNiMn decreases gradually with decreasing grain size. For the sample with a grain size of 2.0 nm, the FCC composition is about 19% at a strain of 20%, accompanied by severe amorphization. The inverse Hall-Petch effect is observed for nanocrystalline CoCrFeNiMn high-entropy alloy in the present simulations. The atomic snapshot of CoCrFeNiMn with a grain size of 2.0 nm under the uniaxial strain confirms that the grain shape change, stacking fault formation, and amorphization are important mechanisms of plastic deformation in nanocrystalline high-entropy CoCrFeNiMn.
The Growth of Triticale (Triticosecale wittm.) in Multi-Metal Contaminated Soils by Use of Zeolite: A Pilot Plant Study

Heavy metals are the most common form of environmental pollution and the evaluation of heavy metal contaminated soils is necessary for reducing the associated risks, making the land resource available for agricultural production, and enhancing food security. There are 2,000 contaminated sites in Greece, according to a previous survey report issued by the Greek Ministry of Environment, out of which 300 required immediate restoration. This study investigated the effects of Cd, Pb, and Zn on Triticale (Triticosecale wittm.) growth in an above-referenced multi-metal contaminated site. In order to evaluate Triticale growth in metal contaminated soil, Triticale plants were cultivated in pots filled with unpolluted and metal-polluted soils in the absence/ presence of Zeolite as an agent empowering the restoration of pollution and immobilizing heavy metals. The results showed that the Triticale plant in polluted soils with high metal concentrations, namely 4.34, 295 and 1,467 mg/kg for Cd, Pb, and Zn, respectively, can act as a “moderate” accumulator of Zn and as a “weak” accumulator of Pb and Cd; while the presence of 1% Zeolite in multi-metal-polluted soils can significantly contribute to plant growth by limiting the uptake of Cd, Pb, and Zn. This study demonstrated that the addition of 1% Zeolite to multi-metal contaminated soils could minimize metal (Pb, Cd, and Zn) pollution in the environment and positively contribute to the growth of Triticale biomass for use as an animal feed within the context of sustainable development.
Graphene Oxide Tablets for Sample Preparation of Drugs in Biological Fluids: Determination of Omeprazole in Human Saliva for Liquid Chromatography Tandem Mass Spectrometry

In this study, a novel sort of sample preparation sorbent was developed, by preparing thin layer graphene oxide tablets (GO-Tabs) utilizing a mixture of graphene oxide and polyethylene glycol on a polyethylene substrate. The GO-Tabs were used for extraction and concentration of omeprazole (OME) in human saliva samples. The determination of OME was carried out using liquid chromatography-tandem mass spectrometry (LC–MS/MS) under gradient LC conditions and in the positive ion mode (ESI+) with mass transitions of m/z 346.3→198.0 for OME and m/z 369.98→252.0 for the internal standard. Standard calibration for the saliva samples was in the range of 2.0–2000 nmol L−1. Limits of detection and quantification were 0.05 and 2.0 nmol L−1, respectively. Method validation showed good method accuracy and precision; the inter-day precision values ranged from 5.7 to 8.3 (%RSD), and the accuracy of determinations varied from −11.8% to 13.3% (% deviation from nominal values). The extraction recovery was 60%, and GO-Tabs could be re-used for more than ten extractions without deterioration in recovery. In this study, the determination of OME in real human saliva samples using GO-Tab extraction was validated.
Crack Detection Using Improved Spectral Clustering Considering Effective Crack Features

Pavement cracks cause various traffic problems. Therefore, we should repair them properly. Nowadays a variety of crack detection methods in computer vision have been proposed, such as spectral clustering. Principal advantages of this method are robust against road-specific noises. However, the approach is inefficient in terms of processing time. In this paper, we propose improvement of processing performance by sparse matrix.
Fixing Mislabeling by Human Annotators Leveraging Conflict Resolution and Prior Knowledge

According to the "human in the loop" paradigm, machine learning algorithms can improve when leveraging on human intelligence, usually in the form of labels or annotation from domain experts. However, in the case of research areas such as ubiquitous computing or lifelong learning, where the annotator is not an expert and is continuously asked for feedback, humans can provide significant fractions of incorrect labels. We propose to address this issue in a series of experiments where students are asked to provide information about their behavior via a dedicated mobile application. Their trustworthiness is tested by employing an architecture where the machine uses all its available knowledge to check the correctness of its own and the user labeling to build a uniform confidence measure for both of them to be used when a contradiction arises. The overarching system runs through a series of modes with progressively higher confidence and features a conflict resolution component to settle the inconsistencies. The results are very promising and show the pervasiveness of annotation mistakes, the extreme diversity of the users' behaviors which provides evidence of the impracticality of a uniform fits-it-all solution, and the substantially improved performance of a skeptical supervised learning strategy.
Deep Multi-Task Learning Based Urban Air Quality Index Modelling

Obtaining comprehensive air quality information can help protect human health from air pollution. Existing spatially fine-grained estimation methods and forecasting methods have the following problems: 1) Only a part of data related to air quality is considered. 2) Features are defined and extracted artificially. 3) Due to the lack of training samples, they usually cannot achieve good generalization performance. Therefore, we propose a deep multi-task learning (MTL) based urban air quality index (AQI) modelling method (PANDA). On one hand, a variety of air quality-related urban big data (meteorology, traffic, factory air pollutant emission, point of interest (POI) distribution, road network distribution, etc.) are considered. Deep neural networks are used to learn the representations of these relevant spatial and sequential data, as well as to build the correlation between AQI and these representations. On the other hand, PANDA solves spatially fine-grained AQI level estimation task and AQI forecasting task jointly, which can leverage the commonalities and differences between these two tasks to improve generalization performance. We evaluate PANDA on the dataset of Hangzhou city. The experimental results show that our method can yield a better performance compared to the state-of-the-art methods.
Real-Time Auditory Scene Analysis using Continual Learning in Real Environments

Artimli ogrenme ile sahne analizi, farkli duyusal modaliteler kullanarak gecmis deneyimlerden daha once bilgi sahibi olunmayan olaylari, eylemleri ve hatta gurultu modellerini asamali olarak ogrenmek icin durmaksizin gerceklesen bir surectir. Bu calismada, dinamik olarak degisen gercek bir ev ortaminda akustik olaylari asamali olarak ogrenmek icin artimli bir ogrenme sistemine dayanan Isitsel Sahne Analizi (ASA) yaklasimi sunulmustur. Ortamdaki en baskin ses kaynaklari olan olaylar, birden fazla kaynagin bulundugu isitsel sahnede bu kaynaktan elde edilen sinyalleri verimli ve kesintisiz bir sekilde islemek icin bir Ses Kaynagi Yerellestirme (SSL) yontemi ile yer tespiti yapilmaktadir. Gercek zamanli sahne analizinde, ses oruntuleri, bu oruntulerden ses ozniteliklerin cikarilmasi ve oznitelik setinin olusturulmasi icin bu kaynagin akustik sinyal akisindan segmente edilir. Artimli ogrenme, kaynaklardan elde edilen akustik sinyallerden bu oznitelik kumelerinde zaman serisi algoritmasi tabanli olan Gizli Markov Modeli (HMM) kullanilmistir. Ogrenme sureci, Bilinmeyen Olay Algilama (UED), Akustik Olay Tanima (AER) ve Hiyerarsik HMM yontemi kullanarak surekli ogrenmenin performansini degerlendirmek icin cesitli deneyler yapilarak gelistirilmistir. Hiyerarsik HMM iki katmandan olusur: 1) AER'nin her bir olay icin HMM ve olay bazli esik degerleri kullanilarak gerceklestirildigi bir alt katman; ve 2) bir ses onitelik seti icin ilgili alt katman HMM’inden cikartilan proto sembolleri ile ses ozniteliklerinin birlestirilip bir HMM ile bir suphe esk degeri kullanilarak UED’nin gerceklstirildigi bir ust katman. Artimli ogrenme, AER ve UED’e sahip bu sistemin, Yanlis-Olumlu Oranlar, Dogru-Olumlu Oranlar, tanima dogrulugu ve hesaplama suresi gozetilerek birden fazla olayin soz konusu oldugu gercek zamanli ogrenme icin gereken gereksinimleri karsilayacak seviyede oldugunu dogruladik. AER sisteminin etkinligi, yuksek dogruluk ve dokuz farkli ses iceren gercek zamanli ASA'da kisa bir yeniden egitim suresi ile dogrulanmistir.
RP-HPLC METHOD DEVELOPMENT AND VALIDATION FOR THE COMBINATION OF IMIQUIMOD AND SALICYLIC ACID

Objective: The present study was undertaken to develop and validate an RP-HPLC method for the combination of imiquimod and salicylic acid Methods: The method was carried out on Nucleodur C18 (250 mm × 4.6 mm I.D., 5 ? m) using low-pressure gradient elution mode. The mobile phase was used as 30M potassium dihydrogen phosphate and acetonitrile (45:55) pH 6.5 adjusted using ortho-phosphoric acid. The concentration of solvents was 1-20 µg/ml and the volume of injection was 20 mcl with the flow rate of 1.0 ml/min. The absorption maxima of salicylic acid and imiquimod were found 234 nm and 226 nm, respectively. Results: The method was validated and showed the linearity greater than 0.99% and with precision (RSD%<1). The limit of detection (LOD) and limit of quantification (LOQ) of salicylic acid was found to be 0.09756 µg/ml and 0.2956 µg/ml, respectively, and imiquimod was found to be 0.044031 µg/ml and 0.13334 µg/ml, respectively. Conclusion: The method developed in the present study was found to be sensitive, specific, and can be applied for the simultaneous estimation of imiquimod and salicylic acid.
Pathway-based polygene risk for severe depression implicates drug metabolism in CONVERGE

Abstract Background The Psychiatric Genomics Consortium (PGC) has made major advances in the molecular etiology of MDD, confirming that MDD is highly polygenic. Pathway enrichment results from PGC meta-analyses can also be used to help inform molecular drug targets. Prior to any knowledge of molecular biomarkers for MDD, drugs targeting molecular pathways (MPs) proved successful in treating MDD. It is possible that examining polygenicity within specific MPs implicated in MDD can further refine molecular drug targets. Methods Using a large case–control GWAS based on low-coverage whole genome sequencing (N = 10 640) in Han Chinese women, we derived polygenic risk scores (PRS) for MDD and for MDD specific to each of over 300 MPs previously shown to be relevant to psychiatric diagnoses. We then identified sets of PRSs, accounting for critical covariates, significantly predictive of case status. Results Over and above global MDD polygenic risk, polygenic risk within the GO: 0017144 drug metabolism pathway significantly predicted recurrent depression after multiple testing correction. Secondary transcriptomic analysis suggests that among genes in this pathway, CYP2C19 (family of Cytochrome P450) and CBR1 (Carbonyl Reductase 1) might be most relevant to MDD. Within the cases, pathway-based risk was additionally associated with age at onset of MDD. Conclusions Results indicate that pathway-based risk might inform etiology of recurrent major depression. Future research should examine whether polygenicity of the drug metabolism gene pathway has any association with clinical presentation or treatment response. We discuss limitations to the generalizability of these preliminary findings, and urge replication in future research.
Microwave Pretreatment and Enzymolysis Optimization of the Lotus Seed Protein

Pretreatment with a microwave was conducted before enzymolysis and shown to enhance the enzymolysis, which changed the secondary structure of the lotus seed protein. Under high-power microwave irradiation, sub bonds of the protein were broken, causing disaggregation and unfolding of the secondary structure, namely a decrease in the intermolecular aggregate structure and increase in the random coil structure, making the protein bonds susceptible to papain in the enzymolysis. On the other hand, a response surface methodology (RSM) was launched to investigate the influence of the enzymolysis process variables on the DH (degree of hydrolysis). The statistical analysis revealed that the optimized conditions were a protein substrate concentration of 15 g/L, pH of 5.5, enzymolysis temperature of 57 °C, papain amount of 0.5 g/L, and enzymolysis time of 45 min, for which the predicted value of the DH was 35.64%. The results indicated that a microwave also had better potential for applications in the enzymolysis of foods.
Comparative genomic analysis of the IDD genes in five Rosaceae species and expression analysis in Chinese white pear (Pyrus bretschneideri)

The INDETERMINATE DOMAIN (IDD) gene family encodes hybrid transcription factors with distinct zinc finger motifs and appears to be found in all higher plant genomes. IDD genes have been identified throughout the genomes of the model plants Arabidopsis thaliana and Oryza sativa, and the functions of many members of this gene family have been studied. However, few studies have investigated the IDD gene family in Rosaceae species (among these species, a genome-wide identification of the IDD gene family has only been completed in Malus domestica). This study focuses on a comparative genomic analysis of the IDD gene family in five Rosaceae species (Pyrus bretschneideri, Fragaria vesca, Prunus mume, Rubus occidentalis and Prunus avium). We identified a total of 68 IDD genes: 16 genes in Chinese white pear, 14 genes in F. vesca, 13 genes in Prunus mume, 14 genes in R. occidentalis and 11 genes in Prunus avium. The evolution of the IDD genes in these five Rosaceae species was revealed by constructing a phylogenetic tree, tracking gene duplication events, and performing a sliding window analysis and a conserved microsynteny analysis. The expression analysis of different organs showed that most of the pear IDD genes are found at a very high transcription level in fruits, flowers and buds. Based on our results with those obtained in previous research, we speculated that PbIDD2 and PbIDD8 might participate in flowering induction in pear. A temporal expression analysis showed that the expression patterns of PbIDD3 and PbIDD5 were completely opposite to the accumulation pattern of fruit lignin and the stone cell content. The results of the composite phylogenetic tree and expression pattern analysis indicated that PbIDD3 and PbIDD5 might be involved in the metabolism of lignin and secondary cell wall (SCW) formation. In summary, we provide basic information about the IDD genes in five Rosaceae species and thereby provide a theoretical basis for studying the function of these IDD genes.
Ion Channel Expression in Human Melanoma Samples: In Silico Identification and Experimental Validation of Molecular Targets

Expression of 328 ion channel genes was investigated, by in silico analysis, in 170 human melanoma samples and controls. Ninety-one members of this gene-family (i.e., about 28%) show a significant (p < 0.05) differential expression in melanoma- vs. nevi-biopsies, taken from the GEO database. ROC (receiver operating characteristic) analysis selected 20 genes as potential markers showing the highest discrimination ability of melanoma vs. nevi (AUC > 0.90 and p < 0.0001). These 20 genes underwent a first in silico-validation round in an independent patients-dataset from GEO. A second-in silico-validation step was then carried out on a third human dataset in Oncomine. Finally, five genes were validated, showing extremely high sensitivity and specificity in melanoma detection (>90% in most cases). Such five genes (namely, SCNN1A, GJB3, KCNK7, GJB1, KCNN2) are novel potential melanoma markers or molecular targets, never previously related to melanoma. The “druggable genome” analysis was then carried out. Miconazole, an antifungal drug commonly used in clinics, is known to target KCNN2, the best candidate among the five identified genes. Miconazole was then tested in vitro in proliferation assays; it dose-dependently inhibited proliferation up to 90% and potently induced cell-death in A-375 and SKMEL-28 melanoma cells, while it showed no effect in control cells. Moreover, specific silencing of KCNN2 ion channel was achieved by siRNA transfection; under such condition miconazole strongly increases its anti-proliferative effect. In conclusion, the present study identified five ion channels that can potentially serve as sensitive and specific markers in human melanoma specimens and demonstrates that the antifungal drug miconazole, known to target one of the five identified ion channels, exerts strong and specific anti-melanoma effects in vitro.
Glutamatergic Signaling Along The Microbiota-Gut-Brain Axis

A complex bidirectional communication system exists between the gastrointestinal tract and the brain. Initially termed the “gut-brain axis” it is now renamed the “microbiota-gut-brain axis” considering the pivotal role of gut microbiota in maintaining local and systemic homeostasis. Different cellular and molecular pathways act along this axis and strong attention is paid to neuroactive molecules (neurotransmitters, i.e., noradrenaline, dopamine, serotonin, gamma aminobutyric acid and glutamate and metabolites, i.e., tryptophan metabolites), sustaining a possible interkingdom communication system between eukaryota and prokaryota. This review provides a description of the most up-to-date evidence on glutamate as a neurotransmitter/neuromodulator in this bidirectional communication axis. Modulation of glutamatergic receptor activity along the microbiota-gut-brain axis may influence gut (i.e., taste, visceral sensitivity and motility) and brain functions (stress response, mood and behavior) and alterations of glutamatergic transmission may participate to the pathogenesis of local and brain disorders. In this latter context, we will focus on two major gut disorders, such as irritable bowel syndrome and inflammatory bowel disease, both characterized by psychiatric co-morbidity. Research in this area opens the possibility to target glutamatergic neurotransmission, either pharmacologically or by the use of probiotics producing neuroactive molecules, as a therapeutic approach for the treatment of gastrointestinal and related psychiatric disorders.
Abbreviated Development of the Brooding Brittle Star Ophioplocus esmarki

The bilaterally symmetrical, feeding larval stage is an ancestral condition in echinoderms. However, many echinoderms have evolved abbreviated development and form a pentamerous juvenile without a feeding larva. Abbreviated development with a non-feeding vitellaria larva is found in five families of brittle stars, but very little is known about this type of development. In this study, the external anatomy, ciliary bands, neurons, and muscles were examined in the development of the brooded vitellaria larva of Ophioplocus esmarki. The external morphology throughout development shows typical vitellaria features, including morphogenetic movements to set up the vitellaria body plan, an anterior preoral lobe, a posterior lobe, transverse ciliary bands, and development of juvenile structures on the mid-ventral side. An early population of neurons forms at the base of the preoral lobe at the pre-vitellaria stage after the initial formation of the coelomic cavities. These early neurons may be homologous to the apical neurons that develop in echinoderms with feeding larval forms. Neurons form close to the ciliary bands, but the vitellaria larva lacks the tracts of neurons associated with the ciliary bands found in echinoderms with feeding larvae. Additional neurons form in association with the axial complex and persist into the juvenile stage. Juvenile nerves and muscles form with pentamerous symmetry in the late vitellaria stage in a manner similar to their development within the late ophiopluteus larva. Even though O. esmarki is a brooding brittle star, its developmental sequence retains the general vitellaria shape and structure; however, the vitellaria larvae are unable to swim in the water column.