Miracle-dz/UniFAR-FTUs huggingface dataset:
Cell-Free Supernatant of Bacillus Strains can Improve Seed Vigor Index of Corn (Zea mays L.) Under Salinity Stress

Currently, salinity is the second biggest challenge in the world after drought and affects all stages of plant growth. The use of environmentally friendly methods such as microorganisms and their derivatives can reduce the destructive effects of salinity stress. A growth chamber experiment was conducted to determine the effects of cell-free supernatant (CFS) from Bacillus strains on germination of corn under salinity stress. Corn seeds were subjected to three salinity levels (0, 100 and 150 mM of NaCl), cell-free supernatant of Bacillus strains (U35, U47, U48, U49, and U50) at two levels of dilution (1:50 and 1:250). Germination percentage and rate decreased with increasing salinity toward 150 mM NaCl all together leading to suppressed growth variables for corn seed seedlings including fresh and dry weight of radicle (47.71 and 52.63%, respectively), and shoot (49.52 and 49.25%, respectively), radicle and shoot lengths (39.90 and 66.07%, respectively). Seed vigor index also decreased by 63.04% at 150 mM NaCl. Contrary to salinity, the CFSs of Bacillus strains increased all the growth traits of corn seeds and reduced the negative effects of salinity, especially severe salinity. Ratios of 1:50 and 1: 250 gave best performance for CFSs from U35 and U50, respectively. In general, the highest seed vigor index was obtained by application of 1: 250 CFS from U50. Most germination traits and seed vigor index correlated significantly positive; however, mean germination time was negatively and significantly correlated with the seed vigor index of corn. The results showed that cell-free supernatant use, may as well-helped in changing the ratios of phytohormones, ROS, the activity of antioxidant enzymes and osmotic proteins, hence reduce the negative effects of salinity and improve seed vigor index which eventually increases the ability of plant seedling establishment under saline conditions.
Soluble C-Type Lectin-Receptor Ligands Stimulate ROS Production in Dendritic Cells and Potentiate Killing of MRSA as Well as the MRSA Induced IL-12 Production

Methicillin resistant Staphylococcus aureus (MRSA) has developed resistance to most β-lactam antibiotics leaving few treatment options against infections with MRSA. Through mannose receptors, mannan potentiates IL-12 production induced by Gram-positive bacteria, a cytokine crucial in the clearance of S. aureus infection. We investigated the IL-12 potentiating effect of mannan pre-treatment of bone marrow-derived dendritic cells prior to stimulation with clinical MRSA strains. Mannan almost doubled IL-12 as well as IFN-β production in response to USA300, also when USA300 was treated with the β-lactam cefoxitin. The MRSA-induced IL-12 production was dependent on bacterial uptake and reactive oxygen species (ROS). Mannan alone induced ROS production, and in combination with USA300, the ROS produced corresponded to the sum induced by mannan and USA300. Addition of a monoclonal antibody against the mannose receptor likewise enhanced USA300-induced IL-12 and induced ROS production. Mannan addition further increased the endocytosis as well as the rate of endosomal killing of bacteria. Pre-treatment with soluble β-glucans also induced ROS and potentiated the USA300-induced IL-12 indicating that other C-type receptors may play a similar role. In the presence of the pro-inflammatory mediators, GM-CSF or IFN-γ, the mannan-enhanced IL-12 production increased further. The USA300-induced and the mannan-facilitated enhanced IFN-β and IL-12 showed same dependency on MAPK c-Jun N-terminal kinase signaling, suggesting that mannan enhances the signals already induced by the bacteria, rather than changing them. We suggest that the C-type lectin-induced ROS production is a key factor in the IFN-β and IL-12 potentiation.
EXONIZATION BY THE EMERGENCE OF A CLEAVAGE-POLYADENYLATION SITE

Exonization is the evolutionary process of recruitment of new exonic regions from previously intronic regions. It is a major contributor to the increased complexity of alternative splicing. Here, we explore exonization mediated by the emergence of a novel cleavage-polyadenylation site in an intron. In Xenopus laevis, the tpm1 gene, which encodes muscular tropomyosin, contains alternative terminal exons. In adult muscles and embryonic hearts, exon 9A is joined to the terminal exon 9B. In embryonic somites, it is joined to the exonic region 9’, which is transcribed from the intron immediately downstream of exon 9A. Consequently, exon 9A is either an internal exon when ligated to exon 9B, or a part of a terminal exon along with region 9’. We show here that region 9’ is present only in amphibians and coelacanths. This suggests that it emerged in sarcopterygians and was lost in amniotes. We used antisense morpholino oligonucleotides to mask the regions of tpm1 pre-mRNA that potentially regulate the inclusion of exon 9A9’. This revealed that the definition of exon 9A9’ relies on a weak cleavage-polyadenylation site and an intronic enhancer, but is independent of the 3’ splice site. We demonstrate that RNAs containing exon 9B are toxic in somites. This may have contributed to the evolutionary pressure that led to the exonization of region 9’ in sarcopterygians. These findings reveal the emergence of a novel cleavage-polyadenylation site that avoids the accumulation of a toxic RNA as a novel mechanism for exonization-mediated diversification of terminal exons.
Long liveTCI !

Correspondence Professor Nick Holford, Dept Pharmacology & Clinical Pharmacology, 85 Park Road. Auckland 1042, New Zealand. Email: n.holford@auckland.ac. nz Twenty years ago, target concentration intervention (TCI) was distinguished from therapeutic drug monitoring (TDM). It was proposed that TCI would bring more clinical benefit because of the precision of the approach and the ability to link TCI to principles of pharmacokinetics and pharmacodynamics to predict the dose required by an individual (1). We examine the theory and clinical trial evidence supporting the benefits of TCI over TDM and conclude that in the digital age TDM should be abandoned and replaced by TCI.
Takotsubo Syndrome: Pathophysiology, Emerging Concepts and Clinical Implications

Takotsubo syndrome is a condition characterized by acute transient left ventricular systolic dysfunction, which at presentation can be challenging to distinguish from acute myocardial infarction. Although previously thought to be a benign, self-limiting condition, recent studies have confirmed that patients with takotsubo syndrome have persistent subtle ongoing cardiac dysfunction, and many continue to have limiting symptoms despite restoration of left ventricular ejection fraction. Moreover, these patients have a substantial burden of morbidity and mortality, as well, with high rates of subsequent major adverse cardiovascular events that approach those of patients with acute coronary syndrome. The mechanisms behind this condition remain elusive. Despite substantial research, the medical community continues to have an incomplete understanding of its underlying pathogenesis and pathophysiology. Catecholamine-induced myocardial injury is the most established and well-known theory, but this does not explain all the clinical features and presentations of the condition, and numerous other pathways and abnormalities are emerging. Because of the poor understanding of its underlying pathophysiology, there is a lack of evidence-based interventions to treat the acute episode, to avoid recurrences, and to prevent major adverse cardiovascular events. This highlights the need for further research to gain a better understanding of the underlying pathophysiology to inform appropriate randomized controlled trials of interventions targeting the causative pathways. Only then can evidence-based management strategies be established to improve clinical outcomes of this potentially lethal condition.
Map-Matching on Low Sampling Rate Trajectories through Frequent Pattern Mining

Map-matching, an important preprocessing task in many location-based services (LBS), projects each point of the global positioning system (GPS) within a trajectory dataset onto a digital map. The state-of-the-art map-matching algorithms typically employ Hidden Markov model (HMM) via shortest path computation. But the computation of the shortest path might not work well on low-sampling-rate trajectory data (e.g., one GPS point every 1–5min), leading to low matching precision and high running time. To solve the problem, this paper ﬁrstly identiﬁes frequent patterns (FPs) in historical trajectories to capture meaningful mobility behaviors, and then extracts mobile behavior criterion (MBC) of mobile users. Such a criterion generally represents the route choice of mobile users on road networks. Moreover, the temporal information within trajectory data was employed to estimate the speed of mobile users on road segments. The identiﬁed FPs, coupled with MBC and moving speed, help to improve the map-matching precision of low-sampling-rate trajectories. In addition, an FP-forest structure was proposed to index the identiﬁed FPs. The structure could greatly speed up the lookup of frequent paths for shorter running time. Furthermore, the FP-forest structure was pruned to reduce redundancy with smaller space cost. Finally, experiments were carried out on real-world datasets. The results conﬁrm that our FP-matching method outperforms state-of-the-art in terms of eﬀectiveness and eﬃciency.
INVESTIGATING INFORMATION LITERACY IN BUSINESS MAJORS

This is a study on information literacy (IL) in Business Majors. A Web-based questionnaire with used to investigate undergraduate Business students on their understanding of IL and assessment of their respective abilities and skills. The study used IL standards adopted by the Association of College and Research Libraries (ACRL). The study adopted the UTAUT model’s as a theoretical framework. The findings conveyed that external UTAUT factors (Social Factors and Facilitating Conditions) have positive effect on IL. Moreover, the findings emphasized the importance of the four factors and suggested the IL could be assessed in all contexts. Implications for discipline and practice are shared.
Commonsense Knowledge Transfer for Pre-trained Language Models

Despite serving as the foundation models for a wide range of NLP benchmarks, pre-trained language models have shown limited capabilities of acquiring implicit commonsense knowledge from self-supervision alone, compared to learning linguistic and factual knowledge that appear more explicitly in the surface patterns in text. In this work, we introduce commonsense knowledge transfer, a framework to transfer the commonsense knowledge stored in a neural commonsense knowledge model to a general-purpose pre-trained language model. It first exploits general texts to form queries for extracting commonsense knowledge from the neural commonsense knowledge model and then refines the language model with two self-supervised objectives: commonsense mask infilling and commonsense relation prediction, which align human language with the underlying commonsense knowledge. Empirical results show that our approach consistently improves the model's performance on downstream tasks that require commonsense reasoning. Moreover, we find that the improvement is more significant in the few-shot setting. This suggests that our approach helps language models better transfer to downstream tasks without extensive supervision by injecting commonsense knowledge into their parameters.
How Multilingual are English Pretrained Models?

English pretrained language models, which 001 make up the backbone of many modern NLP 002 systems, require huge amounts of unlabeled 003 training data. These models are generally 004 presented as being trained only on English 005 text but have been found to transfer surpris-006 ingly well to other languages. We investigate 007 this phenomenon and find that common En-008 glish pretraining corpora actually contain sig-009 nificant amounts of non-English text: even 010 when less than 1% of data is not English (well 011 within the error rate of strong language classi-012 fiers), this leads to hundreds of millions of non-013 English tokens in large-scale datasets. We then 014 demonstrate that even these small amounts of 015 data facilitate cross-lingual transfer for models 016 trained on them and that target language perfor-017 mance strongly correlates with the amount of 018 in-language data seen during pretraining. 019
Pharmacologic inhibition of Mnks in acute myeloid leukemia

The Ras/Raf/MAPK and PI3K/Akt/mTOR pathways are key signaling cascades involved in the regulation of cell proliferation and survival, and have been implicated in the pathogenesis of several types of cancers, including AML. The oncogenic activity of eIF4E driven by Mnk kinases is a convergent determinant of the two cascades, suggesting that targeting the Mnk/eIF4E axis may provide therapeutic opportunity for the treatment of cancer. Herein, a potent and selective Mnk2 inhibitor MNKI-85, and a dual-specific Mnk1 and Mnk2 inhibitor MNKI-19, both derived from a thienopyrimidinyl chemo-type, were selected to explore their anti-leukemic properties. MNKI-19 and MNKI-85 are effective in inhibiting the growth of AML cells which possess an M5 subtype with FLT3-ITD mutation. Further mechanistic studies show that the downstream effects with respect to the selective Mnk1/2 kinase inhibition in AML cells causes G 1 cell cycle arrest followed by induction of apoptosis. MNKI-19 and MNKI-85 demonstrate similar Mnk2 kinase activity and cellular anti-proliferative activity, but exhibit different time-dependent effects on cell cycle progression and apoptosis. Collectively, this study shows that pharmacologic inhibition of both Mnk1 and Mnk2 can result in a more pronounced cellular response than targeting Mnk2 alone. MNKI-85, a first-in-class inhibitor of Mnk2, however, can be used as a powerful pharmacologic tool in studying the Mnk2/eIF4E-mediated tumorigenic mechanism. In conclusion, this study provides a better understanding of the mechanism underlying the inhibition of AML cell growth by Mnk inhibitors and suggests their potential utility as a therapeutic agent for AML.
Deep Q-Learning in Traffic Signal Control: A Literature Review

Traffic congestion is a complex problem with far-reaching economic, environmental and societal impacts. Of particular interest are urban intersections, which have become traffic bottlenecks due to badly timed traffic signal plans. In recent years, intelligent traffic signal control based on connected vehicle technology is on the rise. Particularly reinforcement learning (RL) approaches are seen as a promising method to adaptively control intersections in real-time. RL for traffic signal control is a fast-developing field, with many new traffic controllers being proposed rapidly. This paper conducts a systematic literature review on the state-of-the-art in traffic signal control (TSC) for the most commonly applied RL method: deep Q-learning. The review discusses different design choices researchers have to make when designing a new reinforcement learning-based traffic signal controller. Specifically, the paper discusses environment specifications (network topologies, traffic movements and phases), agent specifications (states, actions, rewards, model extensions), and other specifications (traffic generation, performance indicators, base cases). Furthermore, the review identifies open research gaps and makes suggestions for future research. The paper concludes that much of the design process of current RL-based traffic signal controllers is trial-and-error based, without clear guidelines or best practices regarding agent design. To facilitate better systematic comparisons between proposed agents, it is highly suggested to develop standardized environments with standardized scenarios in order to benchmark controllers. This will allow for faster development and evaluation.
Rotten Apples Spoil the Bunch: An Anatomy of Google Play Malware

This paper provides an in-depth analysis of Android malware that bypassed the strictest defenses of the Google Play application store and penetrated the official Android market between January 2016 and July 2021. We systematically identified 1,238 such malicious applications, grouped them into 134 families, and manually analyzed one application from 105 distinct families. During our manual analysis, we identified malicious payloads the applications execute, conditions guarding execution of the payloads, hiding techniques applications employ to evade detection by the user, and other implementation-level properties relevant for automated malware detection. As most applications in our dataset contain multiple payloads, each triggered via its own complex activation logic, we also contribute a graph-based representation showing activation paths for all application payloads in form of a control- and data-flow graph. Furthermore, we discuss the capabilities of existing malware detection tools, put them in context of the properties observed in the analyzed malware, and identify gaps and future research directions. We believe that our detailed analysis of the recent, evasive malware will be of interest to researchers and practitioners and will help further improve malware detection tools.
Cloud properties over the Southern Ocean during the MARCUS field 1 campaign 2 3

To investigate the cloud properties over the Southern Ocean (SO), the MARCUS field 11 campaign (41 to 69 oS; 60 to 160 oE) was conducted from October 2017 to March 2018, using 12 ship-based measurements. To examine cloud properties over the mid-latitude and Polar regions, 13 the study domain is separated into northern (NSO) and southern (SSO) parts of the SO with a 14 demarcation line of 60 °S. The total cloud fractions (CFs) were 77.9 %, 67.6 %, and 90.3 % for 15 the entire domain, NSO and SSO, respectively, indicating that higher CFs were observed in the 16 Polar region. Low-level clouds, deep cumulus, and shallow cumulus clouds are the three most 17 common cloud types over the SO. For single-layered low-level clouds, mixed-phase clouds 18 dominate with an occurrence frequency (Freq) of 54.5 %, while the Freq of the liquid and ice 19 clouds were 10.1 % (most drizzling) and 17.4 % (least drizzling). The meridional distributions of 20 low-level cloud boundaries are nearly independent of latitude, whereas the cloud temperatures 21 increased ~ 8 K and atmospheric precipitable water vapor increased from ~5 mm at 69 S to ~18 22 mm at 43 S. The mean cloud liquid water paths over NSO were much larger than those over SSO. 23 https://doi.org/10.5194/amt-2021-388 Preprint. Discussion started: 17 January 2022 c © Author(s) 2022. CC BY 4.0 License.
Phylogenomics and Comparative Genomics Highlight Specific Genetic Features in Ganoderma Species

The Ganoderma species in Polyporales are ecologically and economically relevant wood decayers used in traditional medicine, but their genomic traits are still poorly documented. In the present study, we carried out a phylogenomic and comparative genomic analyses to better understand the genetic blueprint of this fungal lineage. We investigated seven Ganoderma genomes, including three new genomes, G. australe, G. leucocontextum, and G. lingzhi. The size of the newly sequenced genomes ranged from 60.34 to 84.27 Mb and they encoded 15,007 to 20,460 genes. A total of 58 species, including 40 white-rot fungi, 11 brown-rot fungi, four ectomycorrhizal fungi, one endophyte fungus, and two pathogens in Basidiomycota, were used for phylogenomic analyses based on 143 single-copy genes. It confirmed that Ganoderma species belong to the core polyporoid clade. Comparing to the other selected species, the genomes of the Ganoderma species encoded a larger set of genes involved in terpene metabolism and coding for secreted proteins (CAZymes, lipases, proteases and SSPs). Of note, G. australe has the largest genome size with no obvious genome wide duplication, but showed transposable elements (TEs) expansion and the largest set of terpene gene clusters, suggesting a high ability to produce terpenoids for medicinal treatment. G. australe also encoded the largest set of proteins containing domains for cytochrome P450s, heterokaryon incompatibility and major facilitator families. Besides, the size of G. australe secretome is the largest, including CAZymes (AA9, GH18, A01A), proteases G01, and lipases GGGX, which may enhance the catabolism of cell wall carbohydrates, proteins, and fats during hosts colonization. The current genomic resource will be used to develop further biotechnology and medicinal applications, together with ecological studies of the Ganoderma species.
Effects of Ultrasonic Treatment on the Structure, Functional Properties of Chickpea Protein Isolate and Its Digestibility In Vitro

This study evaluated the effects of different levels of ultrasonic power (200, 400, 600 W) and treatment time (0, 10, 15 and 30 min) on the structure, emulsification characteristics, and in vitro digestibility of chickpea protein isolate (CPI). The changes in surface hydrophobicity of CPI indicated that ultrasound treatment exposed more hydrophobic amino acid residues. The analysis of sulfhydryl content and zeta potential showed that ultrasound caused the disulfide bond of CPI to be opened, releasing more negatively charged groups, and the solution was more stable. In addition, Fourier Transform Infrared Spectroscopy (FT-IR) and intrinsic fluorescence spectroscopy showed that ultrasound changes the secondary and tertiary structure of CPI, which is due to molecular expansion and stretching, exposing internal hydrophobic groups. The emulsification and foaming stability of CPI were significantly improved after ultrasonic treatment. Ultrasonic treatment had a minor effect on the solubility, foaming capacity and in vitro digestibility of CPI. All the results revealed that the ultrasound was a promising way to improve the functional properties of CPI.
Towards Sustainable Agriculture in China: Assessing the Robust Role of Green Public Investment

This paper reviews the long-term impact of public investments on irrigation and agricultural research and development along with other control variables, including physical capital, irrigated area, fertilizer consumption, level of mechanization, and CO2 emissions on China’s agricultural output from 1986 to 2017. This study applied various econometric methods such as the ARDL bound-testing approach and Johansen co-integration procedure to determine the long-term co-integrating connection amid the variables. The empirical outcomes from the ARDL bound-testing method confirm a long-term co-integrating connection among the variables. The long-run results demonstrated that public investment in agricultural research and development and irrigation have a substantial positive effect on agricultural productivity. Furthermore, results revealed that physical capital and fertilizer consumption also have a significant positive effect on agricultural output; however, CO2 emissions have a substantial negative effect on agricultural production. These findings therefore suggest that the policy makers of China should initiate more effective policies to increase irrigation and agricultural research and development investments. Increasing irrigation and agricultural research and development investments will enhance agricultural productivity by ensuring food security in the country.