bluuebunny/crossref_metadata_2025 huggingface dataset:
Arduino Based Authenticated Voting Machine (AVM) using RFID and Fingerprint for the Student Elections
Authors: Vinayachandra  , Poornima K Geetha , Rajeshwari M , Prasad K Krishna
Published: December 2020

The guiding principles of democracy are free elections. Through elections, people reaffirm their voice, their beliefs, and select someone whose ideas support them most. Voters will elect their representatives via elections. The purpose of the elections is not only to decide the outcome but also to give the winners credence, also for those voters who did not bother to vote for them. The need to hold free, equal, and secret elections is emphasized here. It involves the supervision of elections by free, accountable, impartial and autonomous electoral bodies. As the phrase is ‘today teens, tomorrow’s citizens,’ the student community needs the process of elections to be involved, trained, and acquainted with. Under this respect, the institutions of higher education hold elections in the form of general elections to the Office of the student councils. By this student will receive first-hand information about filing nomination, scrutiny of papers, withdrawing, canvassing, addressing, and most importantly voting. The use of technology in voting will make it easier, more effective, and less prone to breaches of security. Technology will boost and speed up the safety of all votes and make the counting and automated verification much more effective. The design of an advanced voting system is a difficult task as many main requirements have to be met. The secrecy of a poll should be maintained. No proof of which candidate gets particular voting shall be provided by the voting system. The authors implemented the Authenticated Voting Machine in the College elections in this paper to ease the process and improve transparency. The concept is still in its infancy and requires more research to keep it stable and theoretically strong. To ensure protection, the model uses radiofrequency and fingerprint recognition.
Future enhancements and propensities in forthcoming communication system – 5G Network Technology
Authors: Vikranth K. , Anvar Shathik J , Jeetha  , Prasad K. Krishna
Published: December 2020

Network technology and mobile technologies are two essential and booming technologies in today’s scenario that have emerged and quickly evaluated in terms of hardware, communication media, and architecture. Based on the communication system there are massive developments in underlying devices with hardware, software, and entire architecture. All we experienced with 2G, 3G, and 4G communication system, and in the future, we will going to experience next-generation communication system 5G. In underlying technology there have been many improvements and advances, mainly with data transfer speed and unlimited bandwidth that we have never experienced before. Not only is this technology limited to voice and data, but we also expect some IoT revolutions, a system for mobile communication, automated vehicles, industrial and manufacturing automation, human-machine interface, logistics and warehousing, etc. So this 5G technology gives the opportunity for researchers to perform research in related technologies. Here we analyzed the need, concept, service and features of fifth generation communication technologies in this paper. It was proposed the core technology incorporated with 5G and their architecture. Future trends and applications influenced by the 5G communication system were analysed.
Detecting Chronic Kidney Disease from Blood Samples using Neural Networks
Authors: Latheef Mohamed Ghaisan , Logeswaran Rajasvaran , Mohtar Nurul Haniza
Published: December 2020

This paper proposes an artificial neural network approach to automatically detecting Chronic Kidney Disease through fluid samples taken from patients. The rationale for developing such a system is given, as well as possible benefits to the patients and medical industry. Similar systems proposed in the industry and for diagnosing chronic kidney disease through other approaches such as classification algorithms are explored. A dataset to train the neural network on is collected and features analysed, as well as methodology and tools to be used in the development of the neural network.
Public Awareness on How Vape is used as a Tool for Hacking
Authors: Rahman Nor Azlina Abd , Roszlan Mohammad Haziq , Khaled Serry , Alasaad Ameer A.N. , Salem Mohammed
Published: December 2020

Nowadays e-cigarettes and vaping devices are more popular than tobacco cigarettes among the youngsters. Most of the youngsters falsely believe that vaping is safer than tobacco and it is trendier. This research paper is reviewing on how vape is used as a tool for hacking. Based on research, vaping is not only give bad impact to the health but it is also can be used as a medium in transferring malware and to breach the computer system security. A few tweaks and modification of the vape device could make the attacker to transfer the malware to the computer system. Literature review being done on several electronic smoking devices such as e-cigarettes, vaping and JUUL. Statistic on vape users and vape hackers are being done. On top of that questionnaire being prepared and distributed to the public to analyse on public awareness on vape hacking. The method of vape hacking and protection from vaping hackers are also being discuss in this paper. Since vape is using USB to charge the device hence security measures focus more on USB security on how to protect the computer system from the vaping hackers. Several methods can be applied such as disable USB drives and mass storage devices using registry, keep security patches updated, create strong password, control the USB port through device manager or by using a free tool USB drive Disabler/Enabler. There are many others security protection can be implemented but this paper only focuses on several methods as discussed.
Analysis of Surface Quality Measurement With Classification Approach
Authors: Flaih Laith R. , Baha al_Deen Shaimaa Awadh , Ayoobkhan Mohamed Uvaze Ahamed
Published: December 2020

This investigation provides a methodology for surface quality measurement. In machine based vision, an optical inspection is validated to identify defects over materials. As well, normalization approach is used to process homogeneous thickness. With compensation procedures flaws are identified and analyzed. However, after defect identification, decision rules are defected for appropriate classification which offers optimal performance and diminishes tuning complexity. The anticipated approach is effectual and fulfils inspection requirements. Experimental outcomes may validate performance of anticipated approach to recognition rate and inspection speed.
MathFun: Examining the Effectiveness of Calculic Model in Designing App for Dyscalculia Children
Authors: Rohizan Rizawati , Soon Lim Hean , Mubin Siti Azreena
Published: December 2020

Learning disability can vary from dyslexia (reading), dyscalculia (math) and dysgraphia (writing) where it focuses on certain learning disability that is being faced by the children. Dyscalculia is one of the common learning disabilities where in this category children are lack in ability of studying the math. However, with the enhancement of technologies, variety of application can be created in aiding the children learning process such as mobile learning by using mobile app. This paper focuses on examining the design model (Calculic Model) in designing a mobile app for Dyscalculia children. MathFun is a mobile app created by the mobile app developer while following the Calculic Model approach for Malaysia Dyscalculia children. The outcomes of this paper view on the effectiveness of the model towards building a mobile application for these children. Usability was performed in order to assess the usability and verifying the effectiveness of MathFun. This study involved 3 teachers and three children. Descriptive analysis was performed from the collected data. Based on the outcome, it’s shows that by using the suggested model there is an increased in the acceptance and usability of the application by the children.
E-Commerce System for Sale Prediction Using Machine Learning Technique
Authors: Singh Karandeep , Booma P M , Eaganathan Umapathy
Published: December 2020

E-commerce is a platform where people are able to buy and sell goods. The main purpose of e-commerce is to provide convenience to the customers where they do not have to go to a physical store to make a purchase. As the will be able to make the purchase online and the item will be in their door step in the following days. In 2019, a total of $603 billion worth of sales were done via e-commerce in the United States compared to 3.17 billion in retail sales in the United States. The purpose of this study was to build machine learning algorithms which are able to forecast the sales of the e-commerce platform. A research was being done to understand the literature reviews based on similar systems and similar studies that relates to the researcher project. The purpose of doing this literature review is to understand which machine learning model was being used by other studies so the researcher will be able to select some of the best machine learning models for this study. Once the researcher has selected the models, he will them build the models and test their accuracy, error and performance. At the end, the researcher will compare all of the model’s accuracy and errors to get the best model which have low error and high accuracy for forecasting sales. The model which have been fulfil the criteria, will be integrated into the system which is being built by the researcher. The system will give a view of the current and forecasted sales.
An appraisal on the methods and techniques of recommender models for personalised marketing campaigns
Authors: Wong Ann-Nee , Raheem Mafas
Published: December 2020

Recommender models for personalized marketing empower businesses to provide personalized recommendations of goods or services to customers to fulfil their requirements, thus ultimately improves the customer buying experience. Various recommender models powered by robust machine learning algorithms were reviewed on the methods and techniques to appraise its performance concerning the personalized marketing campaigns. Recommender models can be broadly categorized into four types such as content-based, collaborative-based, knowledge-based and hybrid-based. The content-based recommendation is suitable when the system, user or product is new where classification and regression algorithms are mostly implemented. The collaborative-based recommendation is suitable when a more accurate prediction is required where Neighbour-based models, Bayesian methods, rule-based models, decision trees, and latent matrix factorization models may be implemented in this scenario. Knowledge-based recommenders are well suited for recommendations that address explicitly defined user requirements. Different types of recommenders use different sources of data and inherently have different strengths and weaknesses. Selecting the suitable recommender model with the consideration of the scenario and domain of application is very crucial. Therefore, an in-depth research is required and done on the emphasis of the application of recommender models in the personalized marketing especially on the hybrid models with a more efficient deployment for mass applications in this contemporary data-driven business world.
Optimising e-commerce customer satisfaction with machine learning
Authors: Wong Ann-Nee , Marikannan Booma Poolan
Published: December 2020

Customer insighs is the key to the success of e-commerce. Therefore, factors affecting customer satisfaction leading to product purchase and re-purchase should be studied extensively. This study intends to identify the key drivers that influence the satisfaction and the model which can predict the likelihood of customer satisfaction. The outcome would provide insights to prioritise factors that are significant, as well as to provide advice to a wide range of sellers. Four classification machine learning algorithms decision tree, random forest, artificial neural network and support vector machine are evaluated to classify customer satisfaction based on a 3-year historical data from an e-commerce retailer. There were a few challenges with the dataset, such as imbalanced, skewed and missing. Data pre-processing was conducted, and different techniques were evaluated. Of the algorithms evaluated, the best result is achieved by Random Forest with the highest accuracy and reasonable processing time. Meeting the estimated delivery date and the number of days taken to deliver an order is found to be the top two important factors affecting customer satisfaction.
Strategies for reducing the costs of clean-energy technologies in buildings in Nigeria
Authors: Ekung Samuel , Ohama Victor , Ajiero Reginald
Published: December 2020

The costs of clean-energy technologies are currently very high and their adoption in buildings is voluntary. This study evaluated strategies for improving the cost performance of photovoltaic (PV) electricity applied in buildings in Nigeria using a questionnaire survey involving 415 targets. The efficacy of each strategy and consensus in respondents’ perceptions were determined using Fuzzy Set Theory and Kruskal–Wallis tests. The top four strategies for achieving PV-cost reduction are mandating green buildings, standardization of building designs and PV components, facilitating import licensing and massive public education. Developing these strategies to improve the PV value chain will increase the supply capacity of clean energy in emerging markets.
Longitudinal Trajectory of Fatigue in Patients With Inflammatory Bowel Disease: A Prospective Study
Authors: Borren Nienke Z , Long Millie D , Sandler Robert S , Ananthakrishnan Ashwin N
Published: December 2020

Background

Fatigue is a disabling symptom in patients with inflammatory bowel disease (IBD). Its prevalence, mechanism, and impact remain poorly understood. We determined changes in fatigue status over time and identified predictors of incident or resolving fatigue.

Methods

This was a prospective study nested within the IBD Partners cohort. Participants prospectively completed the Multidimensional Fatigue Inventory and the Functional Assessment of Chronic Illness Therapy-Fatigue at baseline, 6 months, and 12 months. A Functional Assessment of Chronic Illness Therapy-Fatigue score ≤43 defined significant fatigue. Multivariable regression models using baseline covariates were used to identify risk factors for incident fatigue at 6 months and to predict the resolution of fatigue.

Results

A total of 2429 patients (1605 with Crohn disease, 824 with ulcerative colitis) completed a baseline assessment, and 1057 completed a second assessment at 6 months. Persistent fatigue (at baseline and at 6 months) was the most common pattern, affecting two-thirds (65.8%) of patients. One-sixth (15.7%) of patients had fatigue at 1 timepoint, whereas fewer than one-fifth (18.5%) of patients never reported fatigue. Among patients not fatigued at baseline, 26% developed fatigue at 6 months. The strongest predictor of incident fatigue was sleep disturbance at baseline (odds ratio, 2.91; 95% confidence interval, 1.48–5.72). In contrast, only 12.3% of those with fatigue at baseline had symptom resolution by month 6. Resolution was more likely in patients with a diagnosis of ulcerative colitis, quiescent disease, and an absence of significant psychological comorbidity.

Conclusions

Fatigue is common in patients with IBD. However, only a few fatigued patients experience symptom resolution at 6 or 12 months, suggesting the need for novel interventions to ameliorate its impact.
New: Jobs Support
Authors: O'Sullivan Darren
Published: December 2020

BCS to launch new jobs board to aid members in their job search. MyBCS also sees updates to include everything needed to prepare for career next steps: from online learning to interview techniques and CV reviews — all in one place.
What is the NIST Framework?
Authors: Cockcroft Steven
Published: December 2020

As global adoption continues, Steven Cockcroft MSc MBCS MCQI CQP explains the origins and rise in popularity of the NIST Cybersecurity Framework, its relevance and implications for organisations and individuals alike.
Success in Security Awareness
Authors: Iaschi Federico
Published: December 2020

Information security culture can aﬀect your business, both good and bad. Federico Iaschi, MBCS CISSP CISM, describes the crucial steps that help develop a successful information security awareness programme.
TOI-257b (HD 19916b): a warm sub-saturn orbiting an evolved F-type star
Authors: Addison Brett C , Wright Duncan J , Nicholson Belinda A , Cale Bryson , Mocnik Teo , Huber Daniel , Plavchan Peter , Wittenmyer Robert A , Vanderburg Andrew , Chaplin William J , Chontos Ashley , Clark Jake T , Eastman Jason D , Ziegler Carl , Brahm Rafael , Carter Bradley D , Clerte Mathieu , Espinoza Néstor , Horner Jonathan , Bentley John , Jordán Andrés , Kane Stephen R , Kielkopf John F , Laychock Emilie , Mengel Matthew W , Okumura Jack , Stassun Keivan G , Bedding Timothy R , Bowler Brendan P , Burnelis Andrius , Blanco-Cuaresma Sergi , Collins Michaela , Crossfield Ian , Davis Allen B , Evensberget Dag , Heitzmann Alexis , Howell Steve B , Law Nicholas , Mann Andrew W , Marsden Stephen C , Matson Rachel A , O’Connor James H , Shporer Avi , Stevens Catherine , Tinney C G , Tylor Christopher , Wang Songhu , Zhang Hui , Henning Thomas , Kossakowski Diana , Ricker George , Sarkis Paula , Schlecker Martin , Torres Pascal , Vanderspek Roland , Latham David W , Seager Sara , Winn Joshua N , Jenkins Jon M , Mireles Ismael , Rowden Pam , Pepper Joshua , Daylan Tansu , Schlieder Joshua E , Collins Karen A , Collins Kevin I , Tan Thiam-Guan , Ball Warrick H , Basu Sarbani , Buzasi Derek L , Campante Tiago L , Corsaro Enrico , González-Cuesta L , Davies Guy R , de Almeida Leandro , do Nascimento Jose-Dias , García Rafael A , Guo Zhao , Handberg Rasmus , Hekker Saskia , Hey Daniel R , Kallinger Thomas , Kawaler Steven D , Kayhan Cenk , S. Kuszlewicz James , Lund Mikkel N , Lyttle Alexander , Mathur Savita , Miglio Andrea , Mosser Benoit , Nielsen Martin B , Serenelli Aldo M , Aguirre Victor Silva , Themeßl Nathalie
Published: December 2020

We report the discovery of a warm sub-Saturn, TOI-257b (HD 19916b), based on data from NASA’s Transiting Exoplanet Survey Satellite (TESS). The transit signal was detected by TESS and confirmed to be of planetary origin based on radial velocity observations. An analysis of the TESS photometry, the Minerva-Australis, FEROS, and HARPS radial velocities, and the asteroseismic data of the stellar oscillations reveals that TOI-257b has a mass of MP = 0.138 ± 0.023 $\rm {M_J}$ (43.9 ± 7.3 $\, M_{\rm \oplus}$), a radius of RP = 0.639 ± 0.013 $\rm {R_J}$ (7.16 ± 0.15 $\, \mathrm{ R}_{\rm \oplus}$), bulk density of $0.65^{+0.12}_{-0.11}$ (cgs), and period $18.38818^{+0.00085}_{-0.00084}$ $\rm {days}$. TOI-257b orbits a bright (V = 7.612 mag) somewhat evolved late F-type star with M* = 1.390 ± 0.046 $\rm {M_{sun}}$, R* = 1.888 ± 0.033 $\rm {R_{sun}}$, Teff = 6075 ± 90 $\rm {K}$, and vsin i = 11.3 ± 0.5 km s−1. Additionally, we find hints for a second non-transiting sub-Saturn mass planet on a ∼71 day orbit using the radial velocity data. This system joins the ranks of a small number of exoplanet host stars (∼100) that have been characterized with asteroseismology. Warm sub-Saturns are rare in the known sample of exoplanets, and thus the discovery of TOI-257b is important in the context of future work studying the formation and migration history of similar planetary systems.
Adjunctive Aspirin vs Placebo in Patients With Schizophrenia: Results of Two Randomized Controlled Trials
Authors: Weiser Mark , Zamora Daisy , Levi Linda , Nastas Igor , Gonen Ilan , Radu Paull , Matei Valentin , Nacu Anatol , Boronin Larisa , Davidson Michael , Davis John M
Published: December 2020

Two previous randomized controlled trials (RCTs) suggested that adjunctive aspirin is efficacious in treating schizophrenia. We conducted two 16-week double-blind randomized placebo-controlled RCTs of adjunctive 1000 mg aspirin vs placebo in schizophrenia. Study 1 included 200 patients, with Positive and Negative Syndrome Scale (PANSS) total score as the primary outcome. Study 2 included 160 patients with C-reactive protein (CRP) >1 mg/L at baseline; the primary outcome was PANSS-positive score. Dropout rates for aspirin/placebo were 12% in study 1 and 20% in study 2. Differences in outcome between aspirin and placebo were calculated with linear regression, adjusting for the baseline value of the outcome. No statistically significant between-group differences were found in primary or secondary outcomes in either study. Study 1: mean difference in PANSS at 16 weeks was −3.9 (95% CI: −8.4 to 0.5, P = .10, effect size (ES) = −0.25) and at 8 weeks was −3.5 (95% CI: −7.5 to 0.5, P = .11, ES = −0.22). Study 2: mean difference in PANSS at 16 weeks was 0.3 (95% CI: −4.1 to 4.7, P = .90, ES = 0.02) and in positive PANSS was 0.5 (95% CI: −1.0 to 2.1, P = .50, ES = 0.11). A meta-analysis of these data with the existing studies, excluding one with large baseline differences in total PANSS, found that the overall estimate of the effect of adjunctive aspirin on the PANSS total score comparing group means at the end of the study was −2.9 (95% CI: −6.6 to 0.7; P = .21), favoring aspirin. Our studies and meta-analysis failed to find a statistically significant improvement in the symptoms of schizophrenia from adjunctive aspirin therapy in comparison to placebo in schizophrenia. Trial registration: study 1: Clinicaltrials.gov: NCT01320982; study 2 (high CRP): EudraCT Number: 2014-000757-36.
Impact of COVID-19 Pandemic on the Outcomes in Patients With Critical Limb Threatening Ischaemia and Diabetic Foot Infection
Authors: Zayed Hany , Musajee Mustafa , Thulasidasan Narayanan , Sayed Mohamed , Francia Federica , Green Meryl , Arissol Martin , Lakhani Alpa , Biasi Lukla , Patel Sanjay
Published: December 2020

Objective:

Examine the impact of COVID-19 pandemic on the outcomes in patients with CLTI or DFI.

Background:

Patients with CLTI and/or DFI are at risk of amputations if not treated in a timely manner.

Methods:

We compared the outcomes in patients with CLTI or DFI during 2 periods; Period 1[P1] (15/03/2019-31/05/2019) and period 2[P2] (15/03/ 2020-31/05/2020- corresponding to COVID-19 pandemic).

Results:

One hundred thirty-nine patients were treated in P1 [mean age 70 years (±11), Male:Female = 102:37] whereas 95 patients were treated in P2 [mean age 67 (±12), Male:Female = 64:31]. The 2 cohorts were matched regarding Rutherford category (P = 0.25) and GLASS classification (P = 0.38). Notably, the time from onset of symptom to clinical presentation was significantly longer [31 (1-105) days vs 27 (0–78) days, (P = 0.017)], whereas the time from presentation to first intervention was significantly shorter [3 (0–61) days vs 5 (0–65) days, (P = 0.013)] in P2 compared to P1. There was a significantly higher white cell count (P = 0.014) and CRP (P = 0.004) on admission in P2. Having treatment for CLTI or DFI in P2 was an independent predictor of worse primary patency rate and freedom from major adverse limb events. At 90 days, amputation-free survival and limb salvage were noticeably worse in P2 compared to P1 (amputation-free survival was 80% and 87% whereas limb salvage was 64% and 72% in P2 and P1, respectively).

Conclusions:

Patients with CLTI and DFI experienced a significantly delayed presentation with features of sepsis on admission in P2. Treatment in P2 was a predictor of worse primary patency and freedom from major adverse limb events and therefore close and long follow-up is advisable.
Automated Analysis of Low-Field Brain MRI in Cerebral Malaria
Authors: Tu Danni , Goyal Manu S. , Dworkin Jordan D. , Kampondeni Samuel , Vidal Lorenna , Biondo-Savin Eric , Juvvadi Sandeep , Raghavan Prashant , Nicholas Jennifer , Chetcuti Karen , Clark Kelly , Robert-Fitzgerald Timothy , Satterthwaite Theodore D. , Yushkevich Paul , Davatzikos Christos , Erus Guray , Tustison Nicholas J. , Postels Douglas G. , Taylor Terrie E. , Small Dylan S. , Shinohara Russell T.
Published: December 2020

A central challenge of medical imaging studies is to extract biomarkers that characterize disease pathology or outcomes. Modern automated approaches have found tremendous success in high-resolution, high-quality magnetic resonance images (MRI). These methods, however, may not translate to low resolution images acquired on MRI scanners with lower magnetic field strength. In low-resource settings where low-field scanners are more common and there is a shortage of radiologists to manually interpret MRI scans, it is critical to develop automated methods that can augment or replace manual interpretation, while accommodating reduced image quality. We present a fully automated framework for translating radiological diagnostic criteria into image-based biomarkers, inspired by a project in which children with cerebral malaria were imaged using low-field 0.35 Tesla MRI. We integrate multi-atlas label fusion, which leverages high-resolution images from another sample as prior spatial information, with parametric Gaussian hidden Markov models based on image intensities, to create a robust method for determining ventricular cerebrospinal fluid volume. We also propose normalized image intensity and texture measurements to determine the loss of gray-to-white matter tissue differentiation and sulcal effacement. These integrated biomarkers have excellent classification performance for determining severe brain swelling due to cerebral malaria.
A quantitative demonstration of NADP+/NADPH redox homeostasis in cyanobacterial cells
Authors: Tanaka Kenya , Shimakawa Ginga , Tabata Hiro , Kusama Shoko , Miyake Chikahiro , Nakanishi Shuji
Published: December 2020

In photosynthetic organisms, it is recognized that the intracellular NADP+/NADPH ratio is regulated within an appropriate range for the cooperative function of a wide variety of physiological processes. However, despite its importance, there is large variability in the values of the NADP+/NADPH ratio quantitatively estimated to date. In the present study, the light-response of the NADP+/NADPH ratio was investigated by applying a novel NADP(H) extraction method using phenol / chloroform / isoamyl alcohol (PCI) in the cyanobacteriumSynechocystissp. PCC 6803. The light-response of NADP(H) observed using PCI extraction was qualitatively consistent with the NADPH fluorescence time course measuredin vivo. Moreover, the results obtained by PCI extraction and the fluorescence-based methods were also consistent in a mutant lacking the ability to oxidize NAD(P)H in the respiratory chain, and exhibiting a unique NADPH light-response. These observations indicate that the PCI extraction method allowed quantitative determination of NADP(H) redox. Notably, the PCI extraction method showed that not all NADP(H) was oxidized or reduced by light-dark transition, indicating that some NADP(H) is not light-responsive. Specifically, 64% of total NADP(H) was observed as non-light-responsive in the wild-type cells. The variation of the intracellular NADP+/NADPH ratio is limited to a narrow range due to the presence of non-light-responsive NADP(H).
A heterogeneously expressed gene family modulates biofilm architecture and hypoxic growth ofAspergillus fumigatus
Authors: Kowalski Caitlin H. , Morelli Kaesi A. , Stajich Jason E. , Nadell Carey D. , Cramer Robert A.
Published: December 2020

The genusAspergillusencompasses human pathogens such asAspergillus fumigatusand industrial powerhouses such asAspergillus niger.In both cases,Aspergillusbiofilms have consequences for infection outcomes and yields of economically important products. Yet, the molecular components influencing filamentous fungal biofilm development, structure, and function remain ill-defined. Macroscopic colony morphology is an indicator of underlying biofilm architecture and fungal physiology. A hypoxia-locked colony morphotype ofA. fumigatushas abundant colony furrows that coincide with a reduction in vertically-oriented hyphae within biofilms and increased low oxygen growth and virulence. Investigation of this morphotype has led to the identification of the causative gene,biofilm architecture factor A (bafA),a small cryptic open reading frame within a subtelomeric gene cluster. BafA is sufficient to induce the hypoxia-locked colony morphology and biofilm architecture inA. fumigatus.Analysis across a large population ofA. fumigatusisolates identified a larger family ofbafgenes, all of which have the capacity to modulate hyphal architecture, biofilm development, and hypoxic growth. Furthermore, introduction ofA. fumigatus bafAintoA. nigeris sufficient to generate the hypoxia-locked colony morphology, biofilm architecture, and increased hypoxic growth. Together these data indicate the potential broad impacts of this previously uncharacterized family of small genes to modulate biofilm architecture and function in clinical and industrial settings.

Importance

The manipulation of microbial biofilms in industrial and clinical applications remains a difficult task. The problem is particularly acute with regard to filamentous fungal biofilms for which molecular mechanisms of biofilm formation, maintenance, and function are only just being elucidated. Here we describe a family of small genes heterogeneously expressed acrossAspergillus fumigatusstrains that are capable of modifying colony biofilm morphology and microscopic hyphal architecture. Specifically, these genes are implicated in the formation of a hypoxia-locked colony morphotype that is associated with increased virulence ofA.fumigatus. Synthetic introduction of these gene family members, here referred to as biofilm architecture factors, in bothA. fumigatusandA. nigeradditionally modulates low oxygen growth and surface adherence. Thus, these genes are candidates for genetic manipulation of biofilm development in Aspergilli.
Biofilm development on urinary catheters promotes the appearance of viable but non-culturable (VBNC) bacteria
Authors: Wilks Sandra A. , Koerfer Verena V. , Prieto Jacqui A. , Fader Mandy , Keevil C. William
Published: December 2020

Catheter-associated urinary tract infections have serious consequences, both for patients and in impacting on healthcare resources. Much work has been carried out to develop an antimicrobial catheter. Although such developments have shown promise under laboratory conditions, none have demonstrated a clear advantage in clinical trials.

Using a range of microbiological and advanced microscopy techniques, a detailed laboratory study comparing biofilm development on silicone, hydrogel latex and silver alloy coated hydrogel latex catheters was carried out. Biofilm development byEscherichia coli, Pseudomonas aeruginosaandProteus mirabilison three commercially available catheters was tracked over time. Samples were examined with episcopic differential interference contrast (EDIC) microscopy, culture analysis and staining techniques to quantify viable but non-culturable (VBNC) bacteria.

Both qualitative and quantitative assessment found biofilms to develop rapidly on all three materials. EDIC microscopy revealed the rough surface topography of the materials. Differences between culture counts and quantification of total and dead cells demonstrated the presence of VBNC populations, where bacteria retain viability but are not metabolically active.

The use of non-culture based techniques showed the development of widespread VBNC populations. These VBNC populations were more evident on silver alloy coated hydrogel latex catheters, indicating a bacteriostatic effect at best. The laboratory tests reported here, that detect VBNC bacteria, allow more rigorous assessment of antimicrobial catheters offering an explanation for why there is often minimal benefit to patients.

IMPORTANCE

Several antimicrobial urinary catheter materials have been developed but, although laboratory studies may show a benefit, none have significantly improved clinical outcomes. The use of poorly designed laboratory testing and lack of consideration to the impact of VBNC populations may be responsible. While the presence of VBNC populations is becoming more widely reported, there remains a lack of understanding of the clinical impact or influence of exposure to antimicrobial products. This is the first study to investigate the impact of antimicrobial surface materials and the appearance of VBNC populations. This demonstrates how improved testing is needed prior to clinical trials uptake.
Inter-breeder differences in prepulse inhibition deficits of C57BL/6J mice in a maternal infection model for schizophrenia
Authors: Kobayashi Yutaro , Inaba Hiroyoshi , Iwakura Yuriko , Namba Hisaaki , Sotoyama Hidekazu , Murata Yui , Iwamoto Kazuya , Nawa Hiroyuki
Published: December 2020

Genetic and environmental factors interact with each other to influence the risk of various psychiatric diseases; however, the intensity and nature of their interactions remain to be elucidated. We used a maternal infection model using polyinosinic-polycytidylic acid (Poly(I:C)) to determine the relationship between the maternal breeding environment and behavioral changes in the offspring. We purchased pregnant C57BL/6J mice from three breeders and administered Poly(I:C) (2 mg/kg) intravenously in their tail vein on gestation day 15. The offspring were raised to 8-12 weeks old and subjected to the acoustic startle tests to measure their startle response intensity, prepulse inhibition levels, and degree of the adaptation of the startle response. No statistical interaction between Poly(I:C) administration and sex was observed for prepulse inhibition; thus, male and female mice were analyzed together. The Poly(I:C) challenge significantly decreased prepulse inhibition levels of the offspring born to the pregnant dams from Breeder A but not those from the other breeders. However, there were no significant inter-breeder differences in Poly(I:C) effects on startle response and on startle adaptation. The rearing environment of mouse dams has a prominent impact on the Poly(I:C)-induced prepulse inhibition deficits in this maternal infection model.
Nanowires unravel a time-correlated stochastic vectorial process in cells
Authors: Nair Vishnu , Seebald Matthew
Published: December 2020

A cell uses its cytoskeletal machinery to control its membrane projections to seek and obtain cargo from its microenvironment. Though this process has been studied extensively using spherical cargo, it remains largely unknown how the process operates with vectorial ones, which are non-spheroid rigid objects with an aspect ratio. In this study, a vectorial cargo, silicon nanowire, was observed to have multiple modes of initial contact and to realign along a membrane projection or on a lamella. Using a qualitative theoretical approach, we demonstrate how membrane energy fluctuations potentially drive this realignment of a vectorial cargo. This was understood by calculations which establish how aspect ratio controls the energy landscape in a vectorial object and its influence on relative energy stability of nanowire-membrane contacts. A study of the realignment transport of vectorial cargoes and their comparison with Ornstein-Uhlenbeck process simulations revealed how one-dimensional time-correlated noise manifested in the transport process. Furthermore, a comparison between sliding of nanowires on cell membrane contacts versus rotational realignment with the same model revealed identical characteristics behind both. The understanding that one-dimensional time-correlated noise underlies both sliding and rotation of a vectorial cargo establishes how cytoskeletal dynamics effectively couples their realignment with subsequent transport for phagocytosis. This work establishes the significance of vectorial cargoes and the nature of underlying vectorial processes that enable their cellular processing.
Overlapping Definitive Progenitor Waves Divide and Conquer to Build a Layered Hematopoietic System
Authors: Freyer Laina , Iturri Lorea , Biton Anne , Perdiguero Elisa Gomez
Published: December 2020

Adult innate immune cells are part of a layered hematopoietic system constructed from definitive hematopoietic stem and progenitor cells (HSPC) with diverse origins during development. One source of HSPC are fetal hematopoietic stem cells (HSC) that provide long-term reconstitution throughout life. However, the extent to which HSC produce mature cellsin uterois only recently being uncovered. This is in part due to the added complexity of an overlapping wave of definitive progenitors that derive from yolk sac erythro-myeloid progenitors (EMP). HSC and EMP are generated from spatiotemporally distinct hemogenic endothelia, yet they both migrate to the fetal liver niche where they co-habitate and are presumed to reach their full potential. Delineation of the respective HSC and EMP pathways towards developmental immune cell differentiation has been confounded by challenges in ontogeny-specific cell labeling. In this study,in vivoinducible pulse chase labeling revealed that HSC contribute little to fetal myelopoiesis and that EMP are the predominant source of mature myeloid cells until birth. This is similar to what has been reported for the erythroid branch of hematopoiesis thereby establishing a developmentally-restricted privilege for erythro-myeloid differentiation from EMP compared to HSC. Tracing the origins of mature cells to the progenitor level by immunophenotyping and single cell RNA sequencing uncovered a dichotomy in the allocation of fetal liver EMP and HSC to myeloid progenitor subsets, both in timing and lineage bias. This has exposed an uncoupling between developmental granulopoiesis and monopoiesis from EMP and HSC pathways, and provides a framework for future studies of HSC-dependent and -independent hematopoiesis.

HIGHLIGHTS

EMP-to-HSC switch in fetal liver myelopoiesis occurs late in gestation

EMP are efficient at producing early transit amplifying erythroid and myeloid intermediates

scRNA-seq reveals three trajectories of EMP myelopoiesis

Myeloid lineage commitment during development is cell type and ontogeny specific
Role of hypothalamic MAPK/ERK signaling in diabetes remission induced by the central action of fibroblast growth factor 1
Authors: Brown Jenny M. , Bentsen Marie A. , Rausch Dylan M. , Phan Bao Anh , Wieck Danielle , Wasanwala Huzaifa , Matsen Miles E. , Acharya Nikhil , Richardson Nicole E. , Zhao Xin , Zhai Peng , Secher Anna , Morton Gregory J. , Pers Tune H. , Schwartz Michael W. , Scarlett Jarrad M.
Published: December 2020

The capacity of the brain to elicit sustained remission of hyperglycemia in rodent models of type 2 diabetes following intracerebroventricular (icv) injection of fibroblast growth factor 1 (FGF1) is well established. Here, we show that following icv FGF1 injection, hypothalamic signaling by extracellular signal-regulated kinases 1 and 2 (ERK1/2), members of the mitogen-activated protein kinase (MAPK) family is induced for at least 24h. Further, we show that in diabetic Lepob/obmice, this prolonged response is required for the sustained antidiabetic action of FGF1, since it is abolished by sustained (but not acute) pharmacologic blockade of hypothalamic MAPK/ERK signaling. We also demonstrate that FGF1 R50E, a FGF1 mutant that activates FGF receptors but induces only transient hypothalamic MAPK/ERK signaling, fails to mimic the sustained glucose lowering induced by FGF1. These data identify sustained activation of hypothalamic MAPK/ERK signaling as playing an essential role in the mechanism underlying diabetes remission induced by icv FGF1 administration.
Cortical stroke produces secondary injury and long-lasting gliosis in the ipsilateral thalamus
Authors: Kim Gab Seok , Stephenson Jessica M. , Al Mamun Abdullah , Wu Ting , Goss Monica G. , Min Jia-Wei , Li Jun , Liu Fudong , Marrelli Sean P.
Published: December 2020

Remote secondary injury in the thalamus has been observed following cortical infarct, however the mechanisms are not well understood. We used the distal MCAO stroke model (pdMCAO) to explore the cellular and temporal gliosis response in secondary thalamic injury in mice. At 3 days post-stroke (PSD3), primary infarct was limited to the cortex, with no infarct in the thalamus. However, at 2 weeks after stroke (PSD14), the ipsilateral thalamus demonstrated degenerating and severely damaged neurons. Staining for GFAP (astrogliosis) or IBA-1 (microgliosis) was first apparent in the ipsilateral thalamus by PSD3, and showed a progressive increase through PSD14. The number of activated microglia was increased within the thalamus at PSD14, reflecting proliferation of resident microglia as well as infiltration of peripheral monocytes. Interestingly, astrogliosis within the thalamus was enduring, as it was still evident at two years post-stroke. Furthermore, the astrogliosis at two years (but not at 6 weeks) demonstrated glial scar-like characteristics. Lastly, we demonstrated that post-stroke treatment with an NMDA receptor antagonist (memantine) reduces gliosis in the thalamus at PSD14. These findings highlight the development of lasting secondary injury in the thalamus following cortical stroke and support the value of memantine treatment in the mitigation of this injury.
The IRE1 Inhibitor Kira6 Curtails The Inflammatory Trait Of Immunogenic Anticancer Treatments By Targeting Hsp60 Independent Of IRE1
Authors: Nicole Rufo , Dimitris Korovesis , Sofie Van Eygen , Derua Rita , Garg Abhishek D , Francesca Finotello , Monica Vara-Perez , Jan Rožanc , Michael Dewaele , de Witte Peter A , Alexopoulos Leonidas G , Janssens Sophie , Lasse Sinkkonen , Thomas Sauter , Verhelst Steven HL , Patrizia Agostinis
Published: December 2020

Cellular stress evoked by immunogenic anticancer treatments engaging the unfolded protein response (UPR) can elicit inflammation with conflicting therapeutic outcomes. To define cell-autonomous mechanisms coupling the UPR to molecular mediators of inflammation, we profiled the transcriptome of cancer cells responding to immunogenic or weakly immunogenic-treatments. Bioinformatics-driven pathway analysis indicated that immunogenic treatments instigated NF-κB/AP-1-inflammatory pathways, which were abolished by the IRE1α-kinase inhibitor KIRA6. Cell-free fractions of chemotherapy and KIRA6 co-treated cancer cells were deprived of pro-inflammatory/chemoattractant factors and failed to mobilize innate immune cells. Strikingly, these potent KIRA6 anti-inflammatory effects were found to be independent of IRE1α. Generation of a KIRA6-clickable photoaffinity probe, mass spectrometry and co-immunoprecipitation analysis identified cytosolic HSP60 as a KIRA6 off-target in the NF-κB pathway. In sum, our study unravels that inflammation evoked by immunogenic treatments is curtailed by KIRA6 independently of IRE1α and further suggests great caution in interpreting the anti-inflammatory action of IRE1α chemical inhibitors.
Potential mammalian species for investigating the past connections between Amazonia and the Atlantic Forest
Authors: Fabrício Machado Arielli , Ritter Camila Duarte , Miranda Cleuton Lima , Pereira Maria João Ramos , Duarte Leandro
Published: December 2020

Much evidence suggests that Amazonia and the Atlantic Forest were connected through at least three dispersion routes in the past: the northeast route, the central route, and the southeast-northwest route. According to previous studies, the southeast-northwest route would have been the most frequently used. However, few studies have assessed the use of these routes based on multiple species. Here we present a compilation of potential mammal species that could have dispersed between the two forest regions to investigate these connections. We evaluate the geographic distributions of mammals occurring in both Amazonia and the Atlantic Forest and the likely connective routes between these forests. We classified the species per habitat occupancy (strict forest specialists, species that prefer forest, or generalists) and compiled the genetic data available for each species to evaluate their potential for phylogeographic studies focusing on genetic exchange between the two forest regions. We found 127 mammalian species occurring in both Amazonia and the Atlantic Forest for which significant genetic data was available. Hence, highlighting their potential for phylogeographic studies investigating the past connections between the two forests. Differently from what was previously proposed, the northeast route showed evidence of past use by more mammal species than the remaining two routes. The central route would have been the second most important in terms of species. Our results show the potential of using mammal species to investigate and bring new insights about the past connections between Amazonia and the Atlantic Forest.
Constructing neural network models from brain data reveals representational transformations underlying adaptive behavior
Authors: Ito Takuya , Yang Guangyu Robert , Laurent Patryk , Schultz Douglas H. , Cole Michael W.
Published: December 2020

The human ability to adaptively implement a wide variety of tasks is thought to emerge from the dynamic transformation of cognitive information. We hypothesized that these transformations are implemented via conjunctive activations in conjunction hubs – brain regions that selectively integrate sensory, cognitive, and motor activations. We used recent advances in using functional connectivity to map the flow of activity between brain regions to construct a task-performing neural network model from fMRI data during a cognitive control task. We verified the importance of conjunction hubs in cognitive computations by simulating neural activity flow over this empirically-estimated functional connectivity model. These empirically-specified simulations produced above-chance task performance (motor responses) by integrating sensory and task rule activations in conjunction hubs. These findings reveal the role of conjunction hubs in supporting flexible cognitive computations, while demonstrating the feasibility of using empirically-estimated neural network models to gain insight into cognitive computations in the human brain.