bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microglia remodelling and neuroinflammation parallel neuronal hyperactivation following acute organophosphate poisoning
Authors: Somkhit Julie , Yanicostas Constantin , Soussi-Yanicostas Nadia 
Published: May 2022

Abstract
Background
Organophosphate (OP) compounds include highly toxic chemicals widely used both as pesticides and as warfare nerve agents. Existing countermeasures are lifesaving but do not alleviate all long-term neurological sequelae, making OP poisoning a public health concern worldwide and the search for fully efficient antidotes an urgent need. OPs cause irreversible acetylcholinesterase (AChE) inhibition, inducing the so-called cholinergic syndrome characterized by peripheral manifestations and seizures associated with permanent psychomotor deficits. Besides immediate neurotoxicity, recent data have also identified neuroinflammation and microglia activation as two processes that likely play an important, albeit poorly understood, role in the physiopathology of OP intoxication and its long-term consequences.
Methods
To gain insight into the response of microglia to OP poisoning, we used a previously described model of diisopropylfluorophosphate (DFP) intoxication of zebrafish larvae. This model reproduces almost all the defects seen in poisoned humans and preclinical models, including AChE inhibition, neuronal epileptiform hyperexcitation and increased neuronal death. Here, we investigated in vivo the consequences of acute DFP exposure on microglia morphology and behaviour, and on the expression of a set of pro- and anti-inflammatory cytokines. We also used a genetic method of microglial ablation to evaluate the role in the OP-induced neuropathology.
Results
We first showed that DFP intoxication rapidly induced deep microglial phenotypic remodelling resembling that seen in M1-type activated macrophages and characterized by an amoeboid morphology, reduced branching, and increased mobility. DFP intoxication also caused massive expression of pro-inflammatory cytokines Il1β and Il8, and, to a lesser extent, immuno-modulatory cytokine Il4, suggesting complex microglial reprogramming that included neuroinflammatory activities. Last, microglia-depleted larvae were instrumental in showing that microglia were major actors in DFP-induced neuroinflammation, and, more importantly, that OP-induced neuronal hyperactivation was markedly reduced in larvae fully devoid of microglia.
Conclusions
DFP poisoning rapidly triggered massive microglia-mediated neuroinflammation probably as a result of DFP-induced neuronal hyperexcitation, which in turn further exacerbated neuronal activation. Microglia are thus a relevant therapeutic target and identifying substances reducing microglial activation could add efficacy to existing OP antidote cocktails.
ToxR is a c-di-GMP binding protein that modulates surface-associated behaviour in Pseudomonas aeruginosa
Authors: Camara Miguel , Dubern Jean , Romero Manuel , Mai-Prochnow Anne , Messina Marco , Trampari Eleftheria , Gijzel Hardeep Naghra-van , Chan Kok-Gan , Carabelli Alessandro , Barraud Nicolas , Lazenby James , Chen Ye , Robertson Shaun , Malone Jacob , Williams Paul , Heeb Stephan 
Published: May 2022

Abstract
Pseudomonas aeruginosa uses multiple protein regulators that work in tandem to control the production of a wide range of virulence factors and facilitate rapid adaptation to diverse environmental conditions. In this opportunistic pathogen, ToxR was known to positively regulate the production of the major virulence factor exotoxin A and now, through analysis of genetic changes between two sublines of P. aeruginosa PAO1 and functional complementation of swarming, we have identified a previously unknown role of ToxR in surface-associated motility in P. aeruginosa. Further analysis revealed that ToxR had an impact on swarming motility by regulating the Rhl quorum sensing system and subsequent production of rhamnolipid surfactants. Additionally, ToxR was found to tightly bind cyclic diguanylate (c-di-GMP) and negatively affect traits controlled by this second messenger including reducing biofilm formation and the expression of Psl and Pel exopolysaccharides, necessary for attachment and sessile communities’ matrix scaffolding, in P. aeruginosa. Moreover, a link between the post-transcriptional regulator RsmA and toxR expression via the alternative sigma factor PvdS, induced under iron-limiting conditions, is established. This study reveals the importance of ToxR in a novel sophisticated regulation of free-living and biofilm-associated lifestyles, appropriate for establishing acute or chronic P. aeruginosa infections.
Modeling the effect of feed gas perturbation on CO2 removal using potassium glycinate in a membrane contactor
Authors: Ghasem Nayef 
Published: May 2022

Abstract
Gaseous-solvent membrane absorption process is a smart approach for removing impurities such as CO2 present in natural gas, flue gas, and biogas into aqueous solvents. Potassium glycinate solvent has better CO2 absorption performance compared to traditional solvents. However, hollow fiber membrane design has limitations, as the presence of the membrane adds additional resistance to mass transfer compared to conventional solvent absorption. To reduce the effect of this additional resistance, it is necessary to increase the mass transfer in the gas and solvent phase boundary layers. This study aims to increase the mass transfer in the gas phase layer without interfering with membrane structure by oscillating the velocity of the feed gas. Consequently, an unsteady state mathematical model was developed and solved using Comsol Multiphysics. The simulation results reveal an optimal oscillation frequency that enables high CO2 removal to be achieved. Under specific operating conditions and without feeding disturbance, the maximum removal rate was about 30%. Applying a feed gas oscillation frequency of 0.05 Hz doubles this to about 70% for CO2 removal.
Biodegradation of the Cyanotoxin Cylindrospermopsin using Bacillus cereus, Micrococcus luteus and Alcaligenes faecalis
Authors: Peduruarachchi H.T , Y Liyanage G. , Idroos F.S. , Ekanayake E. M. , Manage P.M. 
Published: May 2022

Abstract
Cylindrospermopsin (CYN) is one of the most prevalent cyanotoxins, which has the potential to inhibit protein synthesis posesing a risk to human health. Conventional water treatment procedures such as flocculation, coagulation, and heating at 100°C will not completely remove CYN due to its heat stability. Hence, contamination of water sources with CYN creates a challenge to provide safe drinking water. The present study focused on the biodegradation of CYN employing four bacterial strains: Bacillus cereus-Y, Bacillus cereus-S, Micrococcus luteus, and Alcaligenes faecalis, which had previously been identified from water sources for degrading toxins, textile dyes, and hydrocarbons. High-Performance Liquid Chromatography (HPLC) was carried out to study the CYN degradation kinetic studies to identify the best CYN degrader. The study showed that Bacillus cereus-S degraded 29.75 ± 0.24% of the 5.0ppm concentration of CYN after 14 days of incubation, while the other bacterial strains showed significantly low degradation rates (< 11%). Further, kinetic studies revealed that the B. cereus-S degrade three different initial concentrations of CYN: 1.0ppm, 2.5ppm, and 5.0ppm, with removal percentages of 39.06 ± 2.43%, 34.22 ± 1.25%, and 26.35 ± 0.40%, respectively, after 14 days of incubation. For 1.0ppm, 2.5ppm, and 5.0ppm CYN concentrations, the maximum rates of degradation were recorded on the 6th (0.0479 ± 0.0017ppm/day), 8th (0.0402 ± 0.009ppm/day), and 12th (0.0202 ± 0.012ppm/day) days of incubation, respectively. The findings of the study revealed that as the initial CYN concentration decreases, the rate of degradation increases. Compared to the previous literature, the current study shows Bacillus cereus-S, an excellent candidate with degradation capabilities of various CYN concentrations.
In situ long term observation of Dendrophyllia ramea (Linnaeus, 1758)
Authors: Salvati Eva , Provenzani Claudio , D’Ambrosi Andrea , Romano Elena , Santero William , Canese Simonepietro 
Published: May 2022

Abstract
An interesting site for the wider population of the coral Dendrophyllia ramea has been identified south-east of Syracuse (Sicilia Channel, Ionian Sea) at 75 water depth. Dendrophyllia ramea is a poorly known arborescent scleractinian coral, classified as ‘Vulnerable’ according to the Mediterranean IUCN Red List, listed in the Barcelona Convention (Annex B). To increase the knowledge about the ecology of the species, long-term in situ observations were carried out on two colonies using a specific homemade underwater recording system. D. ramea, in analogy with other Anthozoans of different environments, also showed a circadian rhythm of partial opening and closing of the polyps despite being strongly influenced by the intensity of the current. These aspects, of great interest to the ecology of this protected species, will be investigated with the aid of current meters to obtain a quantitative estimate of the intensity of the current. This project gave great results in terms of innovative research as well as the added value of trained GUE divers in these data collection activities, which are otherwise difficult to obtain.
Understanding the Uses, Approaches and Applications of Sentiment Analysis
Authors: Appiahene Peter , Afrifa Stephen , Kyei Emmanuel Akwa , Nimbe Peter 
Published: May 2022

Abstract
Sentiment Analysis (SA) is a field of text mining research that is still evolving. SA is the algorithmic treatment of text's opinions, sentiments, and subjectivity to determine if a text contains negative, positive, or neutral feelings. We present a thorough introduction to sentiment analysis. This approach is deduced in a simple, intuitive manner, and implementation advice is provided. The many types, uses, challenges and techniques for sentiment analysis, as well as examples, are also explored in this study. The major goal of this survey is to provide a near-complete picture of SA techniques and related topics, compare sentiment analysis and social network analysis in the latter section of the paper, highlighting the distinctions and how they can both be used along with brief information.
Gonioscopy-assisted Transluminal Trabeculotomy (GATT) with Scleral or Iris Fixation for Subluxated Intraocular Lenses and Glaucoma
Authors: Sharon Tal , Ben-Haim Liron Naftali , Dar Nimrod , Assia Ehud I , Belkin Avner 
Published: May 2022

Abstract
Purpose – To report on a combined surgical approach of IOL fixation and GATT for the treatment of subluxated IOLs and glaucoma.Methods – In this retrospective cohort, Charts of patients who underwent IOL-fixation combined with GATT between November 2019 and October 2021 were reviewed. Main outcome measure was surgical success, defined as a well-centered IOL and an IOP of 18mmHg or lower and either a 30% IOP reduction or a reduction in medications as compared to baseline. Complications and need for reoperation were recorded.Results – 8 patients who underwent GATT with IOL-fixation were included. Mean age was 80.88 years (range 73-90). The pathomechanism of subluxation for all patients was pseudoexfoliation. 5 cases underwent scleral-fixation, and 3 underwent iris-fixation. Mean follow-up was 6.5 months. The success rate was 100%. Mean baseline IOP was 19.75±6.38 mmHg on 3.38±0.74 medications. 3 patients were on an oral carbonic-anhydrase inhibitor (CAI) prior to surgery. Mean IOP at the end of follow-up was 13.43±4.43 mmHg on 0.63±1.19 medications, and none were on oral CAIs. No intraoperative complications occurred, transient hyphema and vitreous hemorrhage were the most common postoperative complications. All patients had a well-centered IOL. No patients needed any additional surgery. Mean BCVA was 0.62±0.7 at baseline and 0.40±0.31 at the end of follow-up. One patient with advanced glaucoma did not recover her VA, while other patients’ BCVA was either retained or improved.Conclusions – GATT can be combined with IOL-fixation to effectively reduce IOP and medication usage.
Tumor Control and Hearing Preservation after Gamma Knife Radiosurgery for Vestibular Schwannomas in Neurofibromatosis Type 2- A Retrospective Analysis of 133 Tumors GKRS for Vestibular Schwannoma in NF-2
Authors: Kris Gour Surya Sri , Pahwa Bhavya , Jagdevan Aman , Singh Manmohan , Kale Shashank , Agrawal Deepak 
Published: May 2022

Abstract
Purpose
This study was conducted with the aim to estimate long-term tumor control, hearing preservation rates in patients with NF2 related VS, retreatment success rate and assess the associated predictive factors .
Methods
This was a retrospective analysis of NF2 associated VS who underwent GKRS between 2009 and 2020 and had a minimum follow up of 1 year. Loss of tumor control was defined as greater than 10% increase in volume in more than one follow up imaging or the need for retreatment in the form of repeat GKRS or surgery. Kaplan-Meier method was utilized to evaluate Actuarial tumor control and hearing preservation rates.
Results
85 patients with 133 VSs were included in the study. The mean age was 29.8 years. 57 tumors showed tumor regression, 35 showed stable disease and 23 progressed in size at last follow up. Actuarial tumor control rates after 1, 3, 5, and 9 years were 95%, 79%, 75% and 55% respectively with overall tumor control rate being 85%. Hearing worsened in 39 patients and Facial nerve dysfunction occurred in 4 patients. 5 tumors underwent retreatment with GKRS at a median duration of 27.6 months (19–36 months) following the first GKRS.
Conclusion
This is the largest radiosurgical series of NF2 associated VS reported till date. GKRS provides a high rate of long-term local tumor control with a low risk of neurological deprivation for patients with these tumors. The need for retreatment with GKRS although low, is associated with good tumor control and lesser complications.
Deterministic effects of pH in shaping soil resistome revealed by metagenomic analysis
Authors: Liu Zishu , Zhao Yuxiang , Zhang Baofen , Wang Jiaqi , Zhu Lizhong , Hu Baolan 
Published: May 2022

Abstract
Background
Research in environmental resistome has been greatly facilitated by the use of the comprehensive database of antibiotic resistance genes (ARGs). Through this approach, the high prevalence of multidrug efflux pump genes was recently found in various ecosystems and has raised concerns. Since most of the efflux pumps were driven by proton-motive-force (PMF), studying whether soil pH, i.e. proton activity, is a determinant in selecting multidrug efflux pump genes and thus shaping soil resistome is of great interest.
Results
Based on the distribution of soil pH in China, we collected soil samples from forest, cropland and grassland in four typical climatic areas with pH values ranging from 4.37–9.69. ARG profiles of 36 soil metagenomes and 41 metagenome-assembled genomes were obtained by using the SARG database and the ARG-OAPs pipeline. As the result, 264 ARG subtypes associated with 20 classes of antibiotics were identified, while multidrug resistance (69.72% of whole resistome abundances) and efflux pump (82.49%) were the dominant ARG category and resistance mechanism. Independent of sampling location, the abundance of multidrug resistance gene was decreased linearly with increasing pH over the given range, which contributed to almost the entire variation in ARG abundances. In addition, soil pH also determined the diversity, i.e. evenness, of ARGs, and thus explained 75.2% of the resistome variation in the variance partitioning analysis. On this basis, we investigated the relationship between ARGs and bacterial phyla using consistency and correlation analysis, as well as tested their assembly mechanisms using a neutral model, and found ARGs were naturally selected despite the neutral assembly of the bacterial community.
Conclusions
Our results revealed the deterministic effect of pH on shaping soil resistome, and infer that this is related to the selection of PMF-driven multidrug efflux pumps under high proton activity. Such natural changes in background ARGs deserve further attention.
Flow virometry for water-quality assessment: Protocol optimization for a model virus and automation of data analysis
Authors: Bischel Heather , Safford Hannah , Johnson Melis 
Published: May 2022

Abstract
Flow virometry (FVM) can support advanced water treatment and reuse by delivering near real-time information about viral water quality. But realizing the full potential of FVM in relevant applications relevant to water treatment and reuse requires consistent, optimized protocols to facilitate data validation and interlaboratory comparison—as well as approaches to protocol design that can extend the suite of viruses that FVM can feasibly and efficiently monitor. We address these needs herein. First, we optimize a sample-preparation protocol for a model virus using a fractional factorial experimental design. The final protocol for FVM-based detection of T4—an environmentally relevant viral surrogate—blends and improves on existing protocols developed using a traditional “pipeline”-style optimization approach. Second, we test whether density-based clustering can aid and improve analysis of viral surrogates in complex matrices relative to manual gating. We compare manual gating with results obtained through algorithmic clustering: specifically, by coupling the OPTICS (Ordering Points to Identify Cluster Structure) ordering algorithm with either manual or automated extraction of clusters from the OPTICS-ordered data. We demonstrate that OPTICS-assisted clustering can in some cases work as well or better than manual gating of FVM data—and is far faster and less labor-intensive. OPTICS-assisted clustering can also point to features in FVM data that are difficult to detect through manual gating alone. We demonstrate our combined sample-preparation and automated data analysis pipeline on tertiary-treated wastewater samples collected from a water-recycling facility and augmented with T4 and virus-sized fluorescent particles. As use of FVM for viral water-quality assessment expands, we recommend that this protocol be used to validate instrument performance prior to and alongside application of FVM on environmental samples. Widespread adoption of a consistent, optimized analytical approach that (i) centers on a widely available, easy-to-use viral target, and (ii) includes automated data analysis will bolster confidence in FVM as a reliable approach for microbial water-quality monitoring.
Left atrial dissection after a supra-annular mitral valve replacement for endocarditis
Authors: Noue Valentin de Villiers de la , Théry Guillaume , Faroux Laurent , Belkessa Nasreddine , Rubin Sylvain , Mourvillier Bruno , Goury Antoine 
Published: May 2022

Abstract
Background : left atrial dissection is a rare and a potentially fatal complication of cardiac surgery. Multi-modal imagery is helpful for the diagnosis and to guide the treatment.Case presentation : we report the case of a 66-year-old patient who underwent a combined mitral and aortic valve replacement. She underwent a replacement of the aortic and mitral prosthetic valves and the implantation of a leadless pacemaker 4 weeks later because of a paroxystic third-degree atrioventricular block complicating an infectious endocarditis. After the second surgery, she developed a severe pulmonary oedema. The transoesophageal echocardiography revealed a left atrial wall dissection and the apparition of a false aneurysm. A synchronized cardiac CT-scan confirmed a false aneurysm behind the left atrium.Conclusions : multi-modal imagery including transoesophageal echocardiography and cardiac CT-scan is helpful for the diagnosis of left atrial dissection and to guide the treatment.
Deep Learning based IDS for Secured Routing in Wireless Sensor Networks using Fuzzy Genetic Approach
Authors: Subramani Shalini , M Selvi 
Published: May 2022

Abstract
Wireless Sensor Networks (WSNs) are consisting of a number of sensing nodes that are used to collect data from various environmental conditions and are used frequently when it comes to monitoring and regulating of the network environment. In this scenario, the presence of malicious nodes in the network will lead to challenges in the provision of communication security since it is considered as a significant issue in the successful delivery of the acquired data. Therefore, it is necessary to safeguard the network communication from the security threats by identifying the dangerous behaviours in each of the sensor nodes and then by isolating the malicious nodes. This can be accomplished by the deployment of Intrusion Detection Systems (IDSs) at the sensor nodes. However, the existing security systems using IDSs are unable to attain sufficient detection accuracy even though the security models are developed using multiple strategies. To handle this issue, we have proposed a novel Intrusion Detection System (IDS) in this work by using a Convolution Neural Network based Deep Learning (DL) approach along with a fuzzy inference model. In this work, the proposed IDS keeps track of the network and system activities by using a Fuzzy Convolutional Neural Network (F-CNN) which is proposed in this paper to look for signs of malicious activities. In addition to this IDS, we propose a new A-Star search based Neuro-Genetic Secure Routing Algorithm (ASNGSRA) in order to increase the security of communication in WSNs. The proposed ASNGSRA framework also predicts the best optimal route in a secured way from the source to destination. The major advantages of the IDS based secured routing model with neuro-genetic route discovery process proposed in this paper include the increase in security, packet delivery ratio and network lifespan as well as the reduction in delay and energy consumption.
A Multi-Criteria Model For Sustainable Development Goals Using Fuzzy Goal Programming-Application For Egypt
Authors: Elrayes Amani , Badr Elsayed , Seidy Essam El , Rabie Aya 
Published: May 2022

Abstract
Background: Sustainable development necessitates the implementation of policies that integrate various competing economic, environmental, energy, and social objectives. Multi-Criteria Decision Analysis using goal programming is a popular and widely used technique to study decision problems with multiple conflicting objectives. Fuzzy goal programming models are the most appealing choice since real-life situations frequently contain imprecise information. Results: This article proposes fuzzy goal programming model that combines optimal resource allocation with prospective goals for economic development, electricity consumption, employment, and greenhouse gas emission reduction in Egypt's primary economic sectors.The presented model analyses the prospects for improvement, the effort required, and the implementation of sustainable development strategies. The model also offers valuable insights to decision makers for both strategic planning and investment allocations towards sustainable development. We validate the model by applying it to Egypt's important economic sectors to meet the country's 2030 sustainable development goals. Conclusion: The model implies that Egypt's objective of GDP growth will not be met, and that further research and preparation is required. It also recommends that Egypt take some required measures in the direction of renewable technologies, such as solar and wind energy, which have enormous potential for achieving sustainability goals. This can also aid in meeting greenhouse gas emission targets, as well as meeting power consumption targets. The model also provides a quantitative and mathematical reason for additional investments in order to improve Egypt's energy portfolio composition.