bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of Different Solvents in Natural Dyes from Roselle (Hibiscus Sabdariffa) and Green Tea Leaves (Camellia Sinensis) for Dye-Sensitized Solar Cell
Authors: Norhisamudin N. A. , Sabani N. , Shamimin M.M. , Juhari N. , Shaari S. , Ahmad M.F. , Zakaria N.
Published: March 2021

A dye-sensitized solar cell (DSSC) fabricated using anthocyanin or chlorophyll natural dye extract coming from Roselle (Hibiscus Sabdariffa) and Green Tea leaves (Camellia Sinensis). Both dye pigmentations were extracted using different alcohol-based solvent, namely, ethanol, methanol and mixed (ethanol + methanol) to identify whether the different solvents give the effect during the dye extraction. The performance of the electron transfer interaction between the natural dye and Titanium Dioxide (TiO2) was determined. The photovoltaic response of DSSC was collected by recording the data of I-V characteristic under illumination. The DSSC using the Roselle dye extract yielded the following results; Voc = 0.001 V, Jsc = 0.00868(mA/cm2), FF = 0.3554 and η = 0.00142% which is coming from the mixed solvent. On the other hand, the green tea dye extract yielded the following results; Voc = 0.3985, Jsc = 0.000797 (mA/cm2), FF = 0.3985 and η = 0.0000752% which is coming from the methanol solvent.
Applying the Deep Learning Model on an IoT Board for Breast Cancer Detection based on Histopathological Images
Authors: Zahir Shahirah , Amir Amiza , Adilah Hanin Zahri Nik , Ang Wei Chern
Published: March 2021

In breast cancer diagnosis, pathologists evaluate microscopic images of tissue samples to determine if it is benign or malignant. The manual examination process could result in delayed diagnosis, which leads to late cancer treatment and can risk lives. In this paper, we proposed an automated, low-cost, and portable breast cancer detection based on histopathological images by using deep learning. The deep learning models were designed by using the Convolutional Neural Network (CNN). This paper compares the performance of the CNN model by using transfer learning utilizing a pre-trained model (VGG16) and the performance of a CNN model without transfer learning. The result shows that transfer learning provides a good base for classification of histopathological images. The model was successfully deployed on a Raspberry Pi, which demonstrates the model efficiency to run on a lightweight and portable processor.
An Ultra-Wideband CPW Fed Slot Antenna for IoT Applications
Authors: Norlyana Azemi Saidatul , Jiunn Ng Kok , Azmeer Kamarudin Mohamad , Muhammad Nor Che Isa Che , Amir Amiza
Published: March 2021

An Ultra-wideband (UWB) radio is a fast-emerging technology. It is offering several unique attractive features that promotes major advances in wireless communications, networking, imaging, radar and positioning systems. Here, an Ultra-Wideband Coplanar Waveguide fed Monopole antenna for IoT Applications is proposed. The bandwidth of the antenna is enhanced due to the partial rectangular patch and the round corner of the rectangular slot. To validate the simulation results, prototypes of the proposed antenna are fabricated and tested. Based on the results, good agreement has been achieved between the measurement and simulation. The antenna prototype with a total size of 138 mm × 40 mm achieves good impedance matching, constant gain and stable radiation patterns. The impedance bandwidth of the antenna reaches up from 600 MHz to 6.0 GHz for S11 with good omnidirectional radiation performance has also been achieved.
Modelling on Impact of Building Obstruction for V2I Communication Link in Micro Cellular Environment
Authors: Turner J S C , Shahriman A B , Harun A , Murad S A Z , Isa M N , Ismail R C , Ndzi D L , Hashim M S M , Razlan Z M , Wan W K , Ramli M F
Published: March 2021

In vehicular communication, signal transmission in vehicle-to-infrastructure (V2I) mode typically takes place on highways, urban, suburban and rural environments. The presence of buildings in these environments poses a challenge to model path loss (PL) due to multiple propagation mechanisms such as diffractions and reflections. However, very little attention has been made to address building effects on the performance of V2I communication links in microcell environment. This paper investigates signal propagation characteristics caused by the impact of building under micro-cellular environment whereby the base station or road-side-unit (RSU) is usually located under the rooftop of building to allow communication between RSU and mobile station or on-board-unit (OBU) on the road. The goal of this paper is to validate and discuss available path loss models based on effect of building obstruction towards RSU-OBU links specifically in residential housing area. The channel measurements are conducted based on static line-of-sight (LOS) settings of a real-world environment at 2.4 GHz frequency band using IEEE 802.15.4 XBee S2C compliant device to measure its receive power. The results are demonstrated based on received signal strength indicator (RSSI) and root mean square error (RMSE). The attenuation profile is validated and compared with suitable path loss models to evaluate best fit and most compatible model based on our measurements data and environment. The analysis shows that several V2I path loss models and V2V channel models are applicable to be used as a reference to model in LOS microcell environment with building obstruction. The finding shows that PL Urban yields the best fit V2I path loss model in terms of RMSE when compared to our measurement campaign at 2.4 GHz.
Reliable Early Breast Cancer Detection using Artificial Neural Network for Small Data Set
Authors: Vijayasarveswari V. , Jusoh M. , Sabapathy T. , Raof R.A.A. , Khatun S. , Iszaidy I.
Published: March 2021

This paper proposes a breast cancer detection module using Artificial Neural Network for small data set. The developed system consists of hardware and software. Hardware included UWB transceiver and a pair of home- made directional sensor/antenna. The software included a Graphical User Interface (GUI) and k-fold based feed-forward back propagation Neural Network module to detect the tumor existence, size and location along with soft interface between software and hardware. Forward scattering technique is used by placing two sensors diagonally opposite sides of a breast phantom. UWB pulses are transmitted from one side of phantom and received from other side, controlled by the software interface in PC environment. Firstly feed forward backpropagation neural network (FFBNN) is developed. Then, k-fold is combined with developed FFBNN for testing purpose. Four data sets are created where contains 125, 95, 65 and 30 data samples in 1st,2nd,3rd and 4th data set respectively. Collected received signals were then fed into the NN module for training, testing and validation. The process is done for all data sets separately. The system exhibits detection efficiency of tumor existence, location (x, y, z), and size were approximately 87.72%, 87.24%, 83.93% and 80.51% for 1st, 2nd, 3rd and 4th data set respectively. The proposed module is very practical with low-cost and user friendly. The developed breast cancer detection module can be used for large data samples as well as for minimum data samples.
The Performance Analysis of Transfer Learning for Steel Defect Detection by Using Deep Learning
Authors: Abu M , Amir A , Lean Y H , Zahri N A H , Azemi S A
Published: March 2021

Detecting steel surface defects is one of the challenging problems for industries worldwide that had been used in manufacturing quality management. Manual inspection of the steel surface detects is a time-consuming process. This work aims at developing deep learning models that can perform steel defect detection and evaluating the potential of transfer learning for this task. In this paper, four types of transfer learning methods: ResNet, VGG, MobileNet, and DenseNet are experimentally evaluated to develop models for steel surface defect detection. The models were developed for binary classification (defect and no-defect) using the SEVERSTAL dataset from that contains 12,568 images of the steel surface. Then, these models were also assessed for multiclass classification using NEU dataset with 1800 images. In this work, image pre-processing is included to improve the result of steel defects detection. The experimental results have shown that the model developed by using the MobileNet method have the highest detection rate with 80.41% for the SEVERSTAL dataset and 96.94% for the NEU dataset compare to ResNet, VGG, and DenseNet transfer learning.
Correlation of Surface Binary Segmentation and Object Contour Sizing Threshold in Clustering Image Processing
Authors: Hassan M.N. , Kok Wei Kong , Rahim RA , Kahar N.F. , Junita MN
Published: March 2021

Image segmentation and contouring plays a significant role in computer vision. It aims at extracting meaningful objects contained in an image. Obtaining an appropriate threshold value yield a higher accuracy in identifying the specified object of interest. A min-max threshold value was examined for surface binary segmentation and object contour sizing. The binary segmentation threshold (T) suggested to be in the range of 155 to 250 in order to get an appropriate result and the acceptable range for frame divider is between 150 to 250. These results can assist researchers to focus on the applicable threshold value in image processing especially for video analysis.
Donut Modes in Space Wavelength Division Multiplexing: Multimode Optical Fiber Transmission based on Electrical Feedback Equalizer
Authors: Ghazi Alaan , Aljunid S. A. , Zulkarnain Syed Idrus Syed , Endut R. , Ali N. , Amphawan Angela , Fareed Alaa , Al-dawoodi Aras , Noori Awab
Published: March 2021

This study demonstrates the implementation of multi-input-multi-output (MIMO) transmission donut modes in space wavelength division multiplexing (SWDM) over multi-mode optical fiber (MMOF) and simulating the effect of mode coupling of the transmitted signal. However, during the data transmitted over MMF by using SWDM an issue is encountered, which is the inter symbol interference (ISI) due to mode coupling. ISI has been recognized as a major obstacle to high-speed data transmission. The signal processing in SDM of donut modes over MMOF with electrical feedback equalizer is used to improve the performance for increasing the bandwidth. A data rate 80 Gbit/s up for a distance of 1600 meters is achieved. SWDM topology was designed emitted from a spatial vertical cavity surface-emitting laser (VCSEL) through MMOF in conjunction with the configurations of electrical feedback equalizer. The parameters and values used in Opt-Sim simulation topology were listed. The performance measurement of this study based on bit-error rates (BER) and eye diagram before and after electrical feedback equalization were analysed.
FPGA based Quantum Key Distribution Electronic System for Multipurpose Optical Setup and Protocols
Authors: Aseri N. S. M. , Ali N. , Yusof N. R. , Endut R. , Ahmad Hambali N. A. M. , Shahimin M. M. , Rashidi C. B. M. , Aljunid S. A.
Published: March 2021

The purpose of the FPGA electronic control system for Quantum Key Distribution (QKD) is to improve the analog electronic system in optoelectronic conversion. In the existence of the Mezzanine FPGA board, the main conversion of optical laser signal and optical detector signal can be improved. Mezzanine board can reduce the noise errors during the transmission and receiving a signal. Commonly, the optical signal needs to interface with an analog electronic system. This process requires the conversion process and interfacing with a digital signal to control the optical device and produce a good quality optical signal. The Mezzanine board can reduce the uncertainty during signal conversion and gives the digital capability to control the optical devices. The optical modulation signal for phase modulator control can achieve a full complete phase shift in the Mezzanine board. Plus, the voltage phase has capability up to 10 V with an accuracy of 2.4 µV. The time conversion for phase modulator can be extended in the Mezzanine board based on the digital control signal from FPGA. The system is capable to extend into multiple timing control to handle all the signal and to synchronize the signal in receiving, transmission or in between of the transmission. Thus, the system can handle one way or two-way QKD system accordingly.
A Linear 0.98 mV Low-Dropout Voltage Regulator in 0.18-μm CMOS Technology
Authors: Murad S.A.Z. , Harun A. , Isa M.N.M. , Marzuki A. , Sapawi R.
Published: March 2021

This paper presents a linear low-dropout (LDO) voltage regulator in 0.18-pm CMOS technology. The proposed LDO consists of voltage reference, error amplifier, pass device, output capacitor and resistive feedback network. A symmetrical operational transconductance amplifier (OTA) is implemented as an error amplifier and a PMOS transistor is used as a pass device to produce low dropout voltage and low quiescent current. The proposed design is simulated using Spectre simulator in Cadence software to verify its performances. The simulation results indicated that the LDO regulator achieves a regulated output voltage of 1.5 V with the ranges of supply voltage from 1.7 V to 2.0 V. The LDO regulator has a dropout voltage of 19.3 mV under maximum load current of 1.1 mA. The proposed LDO regulator is suitable for power management system.
A Review of Chatbot development for Dynamic Web-based Knowledge Management System (KMS) in Small Scale Agriculture
Authors: Ong R. J. , Raof R. A. A. , Sudin S. , Choong K.Y.
Published: March 2021

Market data indicates that the average age of Malaysian farmers to be 50 years old and that the majorities are in the B40 group. Malaysia have so much of land with a small population of over 30 million compared with neighbours country and yet still need to import over 50 billion in food commodities annually to feed the nation. Small-scale farmers are having issues in communicating with each other and usually lack of Standard Operating Procedure (SOP) compare to industrial farming. An information sharing platform is prominent to disseminate information and knowledge between farmers especially for most of the young farmers who having issues when they newly start to involve in agriculture field. This paper is about to design and develop a framework of dynamic web-based knowledge management system with Chatbot application in order to utilize the information sharing platform to disseminate knowledge and build networks among small-scale farmers and related experts. Thus, information sharing and working together with a related expert will effectively improve both the quality and quantity of the product and also against the diseases on the spot.
Topography characterization of sinusoidal surfaces obtained with electrochemical machining
Authors: Marteau Julie , Anselme Karine , Pieuchot Laurent , Chauvy Pierre-François , Bigerelle Maxence
Published: March 2021

The study and understanding of functionality and its link with surface topography requires surfaces that enable us to decouple the examined effect. The sinusoidal function offers an easy solution for the decoupling of amplitude and frequency. However, the corresponding surfaces would require very good characteristics: shape regularity, low waviness and low microroughness. This study thoroughly characterized sinusoidal surface (egg-box shapes) having periods ranging from 30 μm to 300 μm and peak-to-valley amplitudes comprised between 3 and 30 μm. The microroughness of the examined surfaces was quantified with the arithmetic mean deviation Sa and was found to be around 1 nm for most examined surfaces. The waviness of the surfaces, which was also quantified with Sa, was lower than 0.15 μm for all the surfaces. The relative error computed for the period of the sinusoidal surfaces was lower than 1.3%. Finally, the shape regularity was assessed by comparing the measurements to a mathematical function and the computed average residues were smaller than 0.8 μm. These characteristics highlighted the very good noise-to-signal ratio of the produced surfaces, which can be used in very different fields (biology, mechanics, optics…) to examine topography effect on functionality (cell adhesion, brightness…).
New derivatives of urea-grafted alginate for improving the sorption of mercury ions in aqueous solutions
Authors: A Benettayeb , A Morsli , E Guibal , R Kessas
Published: March 2021

Chemically-modified alginate (obtained by grafting urea on alginate, with different ratios; alginate-urea (1:1) and its new derivatives alginate-urea (1:2) with an exceed of the percent of amino group by 7%) was successfully tested for mercury sorption in aqueous solutions. The influence of pH on metal sorption was first investigated: optimum pH was close to 5.5. Sorption isotherms were modeled using the Langmuir and the Sips equations, and sorption capacity slightly increased with the increased of the % of–NH2 in the sorbent and the maximum sorption capacity exceeded 200 mg Hg l−1 (1.07 mmol Hg g−1; for alginate-urea (1:2)), this means two times the sorption capacity of reference material (i.e., non-modified alginate), and also has a capacity improved compared to alginate-urea (1:1). Under selected experimental conditions the equilibrium was reached with 6–8 h of contact and the kinetic profiles were modeled using the pseudo-first order equation (PFORE), the pseudo-second-order rate equation (PSORE) and the resistance to intraparticle diffusion (RIDE). Surface functional groups, notably; –NH2, –OH and –COOH, were involved in mercury sorption by alginate-urea, suggesting the ion exchange, complexation and/or electrostatic interaction of Hg(II) on the alginate-urea surface. The use of this material, environmentally friendly and simply obtained from a renewable resource, reveals promising for the treatment of low-metal concentration effluents: sorption capacities are comparable to alternative academic and commercials sorbents.
Preparation and characterization of polymeric films based on PLA, PBAT and corn starch and babassu mesocarp starch by flat extrusion
Authors: Rodrigues Samara C S , de Mesquita Fabrício Almeida Silva , de Carvalho Laura H , Alves Tatianny S , Folkersma Rudy , Araújo Regilda S dos R M , Oliveira Amanda D , Barbosa Renata
Published: March 2021

This research aims to evaluate the application of babassu mesocarp starch in the development of polymeric films compared to corn starch widely exploited due to its abundance and worldwide availability. Thus, films based on blends of poly(lactic acid)/poly(butylene adipate-co-terephthalate) (PLA/PBAT) containing commercial corn starch or starch extracted from the babassu mesocarp were developed by means of flat extrusion. The films were characterized and the results indicate that the color, wettability and surfaces depend on the type of starch added. Films containing babassu mesocarp starch present rougher, opaque surfaces with greater water resistance than those with corn starch. The data from this research suggest that both babassu mesocarp and corn starch are alternatives for the production of polymeric films.
Springer motives
Authors: Eberhardt Jens
Published: March 2021

We show that the motive of a Springer fiber is pure Tate. We then consider a category of equivariant Springer motives on the nilpotent cone and construct an equivalence to the derived category of graded modules over the graded affine Hecke algebra.
Expansions of the real field by discrete subgroups of 𝐺𝑙_{𝑛}(ℂ)
Authors: Hieronymi Philipp , Walsberg Erik , Xu Samantha
Published: March 2021

Let

Γ
\Gamma

be an infinite discrete subgroup of Gl

n

(

C

)

_n(\mathbb {C})

. Then either

(

R

,
>
,
+
,
⋅
,
Γ
)

(\mathbb {R},>,+,\cdot ,\Gamma )

is interdefinable with

(

R

,
>
,
+
,
⋅
,

λ

Z

)

(\mathbb {R},>,+,\cdot , \lambda ^{\mathbb {Z}})

for some real number

λ
\lambda

, or

(

R

,
>
,
+
,
⋅
,
Γ
)

(\mathbb {R},>,+,\cdot ,\Gamma )

defines the set of integers. When

Γ
\Gamma

is not virtually abelian, the second case holds.
Thirteen Questions About Using Machine Learning in Causal Research (You Won’t Believe the Answer to Number 10!)
Authors: Mooney Stephen J , Keil Alexander P , Westreich Daniel J
Published: March 2021

Machine learning is gaining prominence in the health sciences, where much of its use has focused on data-driven prediction. However, machine learning can also be embedded within causal analyses, potentially reducing biases arising from model misspecification. Using a question-and-answer format, we provide an introduction and orientation for epidemiologists interested in using machine learning but concerned about potential bias or loss of rigor due to use of “black box” models. We conclude with sample software code that may lower the barrier to entry to using these techniques.
Fine-scale Spatiotemporal Mapping of Asymptomatic and Clinical Plasmodium falciparum Infections: Epidemiological Evidence for Targeted Malaria Elimination Interventions
Authors: Niang Makhtar , Sandfort Mirco , Mbodj Adja Fatou , Diouf Babacar , Talla Cheikh , Faye Joseph , Sane Rokhaya , Thiam Laty Gaye , Thiam Alassane , Badiane Abdoulaye , Vigan-Womas Ines , Diagne Nafissatou , Diene Sarr Fatoumata , Mueller Ivo , Sokhna Cheikh , White Michael , Toure-Balde Aissatou
Published: March 2021

Background

A detailed understanding of the contribution of the asymptomatic Plasmodium reservoir to the occurrence of clinical malaria at individual and community levels is needed to guide effective elimination interventions. This study investigated the relationship between asymptomatic Plasmodium falciparum carriage and subsequent clinical malaria episodes in the Dielmo and Ndiop villages in Senegal.

Methods

The study used a total of 2792 venous and capillary blood samples obtained from asymptomatic individuals and clinical malaria datasets collected from 2013 to 2016. Mapping, spatial clustering of infections, and risk analysis were performed using georeferenced households.

Results

High incidences of clinical malaria episodes were observed to occur predominantly in households of asymptomatic P falciparum carriers. A statistically significant association was found between asymptomatic carriage in a household and subsequent episode of clinical malaria occurring in that household for each individual year (P values were 0.0017, 6 × 10–5, 0.005, and 0.008 for the years 2013, 2014, 2015, and 2016 respectively) and the combined years (P = 8.5 × 10–8), which was not found at the individual level. In both villages, no significant patterns of spatial clustering of P falciparum clinical cases were found, but there was a higher risk of clinical episodes <25 m from asymptomatic individuals in Ndiop attributable to clustering within households.

Conclusion

The findings provide strong epidemiological evidence linking the asymptomatic P falciparum reservoir to clinical malaria episodes at household scale in Dielmo and Ndiop villagers. This argues for a likely success of a mass testing and treatment intervention to move towards the elimination of malaria in the villages of Dielmo and Ndiop.
Inactivation of Blood-Borne Enveloped Viruses with the Nonionic Detergent 2-[4-(2,4,4-Trimethylpentan-2-yl)Phenoxy]Ethanol Does Not Bias Clinical Chemistry Results
Authors: Bailey Adam L , Farnsworth* Christopher
Published: March 2021

Background

Patients infected with virulent pathogens require the sophisticated diagnostic capabilities of a core laboratory for optimal care. This is especially true in outbreaks that strain healthcare system capacity. However, samples from such patients pose an infection risk for laboratory workers. We evaluated a strategy for mitigating this risk by preincubating specimens with 2-[4-(2,4,4-trimethylpentan-2-yl)phenoxy]ethanol, a non-ionic detergent commonly calledTriton X-100.

Methods

Lithium-heparinized plasma was mixed with the detergent Triton X-100 at 1%. Inactivation of Ebola virus (EBOV), yellow fever virus (YFV), and chikungunya virus (CHIKV) was assessed using a virus-outgrowth assay. The impact of 1% Triton X-100 dilution on the components of a complete metabolic panel (CMP) was assessed on a Roche Cobas analyzer with 15 specimens that spanned a large portion of the analytical measurement range.

Results

Incubation with 1% Triton X-100 for 5 min was sufficient to completely inactivate EBOV and YFV spiked into plasma but did not completely inactivate CHIKV infectivity even after 60 min of incubation. This was true only for CHIKV when spiked into plasma; CHIKV was completely inactivated in cell culture medium. A bias of −0.78 mmol/L (95% CI, −2.41 to 0.85) was observed for CO2 and 5.79 U/L (95% CI, −0.05 to 11.63) was observed for aspartate aminotransferase after addition of Triton X-100. No other components of the CMP were affected by the addition of Triton X-100.

Conclusions

Detergent-based inactivation of plasma specimens may be a viable approach to mitigating the risk that certain blood-borne pathogens pose to laboratory workers in an outbreak setting. However, the effectiveness of this method for inactivation may depend on the specimen type and pathogen in question.
Historical industrialisation, path dependence and contemporary culture: the lasting imprint of economic heritage on local communities
Authors: Huggins Robert , Stuetzer Michael , Obschonka Martin , Thompson Piers
Published: March 2021

Culture matters for regional economic development and is one source of cognitive lock-in that influences path creation and dependency. However, little is known about the sources of regional variation in culture. This study explores the long-term imprinting effect of the Industrial Revolution on cultural practices across local communities in Great Britain. Historical data from 1891 on the employment in large-scale industries (e.g. textiles and steel) is used to estimate causal effects of industrialisation on five cultural dimensions. It is found that historical industrialisation is still reflected in contemporary local cultures marked by lower engagement with education and employment, less adherence to social rules but stronger collective action and social cohesion. It is concluded that one reason for the relatively poor effect of the public policies on local and regional economic development is that historical industrialisation has left a lasting legacy on contemporary culture in many places that impairs institutional efforts to foster change.
Suicidal behaviours among deaf adolescents in Ghana: a cross-sectional study
Authors: Quarshie E N B , Fobi D , Acheampong E K , Honu-Mensah C M , Fobi J , Appau O , Andoh-Arthur J , Oppong Asante K
Published: March 2021

Background

A growing global concern is that suicide research has paid little attention to young people with disabilities, particularly, in low- and middle-income countries (LAMICs). We aimed to estimate the 12-month prevalence of suicidal ideation and attempt and describe some associations among deaf adolescents in Ghana.

Methods

This is a cross-sectional anonymous self-report survey involving a nationally representative random sample of 450 school-going deaf adolescents. Data analysis included bivariate and multivariable approaches.

Results

The overall 12-month prevalence of suicidal ideation was 19·3% (95% confidence interval [CI] = 15·8–23·3) and suicidal attempt was 15·6% (95% CI = 12·3–19·2). Although alcohol use and parental divorce were strongly associated with increased odds of both suicidal ideation and attempt, high subjective mental well-being was associated with reduced odds of both suicidal ideation and attempt. Living with no parents and being a final year student were associated with suicidal ideation, while male gender was associated with suicidal attempt.

Conclusions

The prevalence of suicidal behaviours among school-going deaf adolescents in this study compares with estimates among in-school non-deaf adolescents in Ghana and other LAMICs in Africa, and also highlights the need for prevention efforts against the onset of suicidal ideation and possible transition to attempt and suicide among deaf adolescents.
Limited sensitivity and specificity of the ACR/EULAR-2019 classification criteria for SLE in JSLE?—observations from the UK JSLE Cohort Study
Authors: Smith Eve M D , Rasul Sajida , Ciurtin Coziana , Al-Abadi Eslam , Armon Kate , Bailey Kathryn , Brennan Mary , Gardner-Medwin Janet , Haslam Kirsty , Hawley Daniel P , Lane Steven , Leahy Alice , Leone Valentina , Malik Gulshan , Mewar Devesh  , Moots Robert , Pilkington Clarissa , Ramanan Athimalaipet V , Rangaraj Satyapal  , Ratcliffe Annie , Riley Phil , Sen Ethan , Sridhar Arani , Wilkinson Nick  , Beresford Michael W , McCann Liza J , Hedrich Christian M
Published: March 2021

Objectives

This study aimed to test the performance of the new ACR and EULAR criteria, that include ANA positivity as entry criterion, in JSLE.

Methods

Performance of the ACR/EULAR-2019 criteria were compared with Systemic Lupus International Collaborating Clinics (SLICC-2012), using data from children and young people (CYP) in the UK JSLE Cohort Study (n = 482), with the ACR-1997 criteria used as reference standard. An unselected cohort of CYP positive for ANA (n = 129) was used to calculate positive/negative predictive values of the criteria.

Results

At both first and last visits, the number of patients fulfilling the different classification criteria varied significantly (P < 0.001). The sensitivity of the SLICC-2012 criteria was higher when compared with that of the ACR/EULAR-2019 criteria at first and last visits (98% vs 94% for first visit, and 98% vs 96% for last visit; P < 0.001), when all available CYP were considered. The ACR/EULAR-2019 criteria were more specific when compared with the SLICC-2012 criteria (77% vs 67% for first visit, and 81% vs 71% for last visit; P < 0.001). Significant differences between the classification criteria were mainly caused by the variation in ANA positivity across ages. In the unselected cohort of ANA-positive CYP, the ACR/EULAR-2019 criteria produced the highest false-positive classification (6/129, 5%).

Conclusion

In CYP, the ACR/EULAR-2019 criteria are not superior to those of the SLICC-2012 or ACR-1997 criteria. If classification criteria are designed to include CYP and adult populations, paediatric rheumatologists should be included in the consensus and evaluation process, as seemingly minor changes can significantly affect outcomes.
Ancient evolution of hepadnaviral paleoviruses and their impact on host genomes
Authors: Lytras Spyros , Arriagada Gloria , Gifford Robert J
Published: March 2021

Hepadnaviruses (family Hepadnaviviridae) are reverse-transcribing animal viruses that infect vertebrates. DNA sequences derived from ancient hepadnaviruses have been identified in the germline genome of numerous vertebrate species, and these ‘endogenous hepatitis B viruses’ (eHBVs) reveal aspects of the long-term coevolutionary relationship between hepadnaviruses and their vertebrate hosts. Here, we use a novel, data-oriented approach to recover and analyse the complete repertoire of eHBV elements in published animal genomes. We show that germline incorporation of hepadnaviruses is exclusive to a single vertebrate group (Sauria) and that the eHBVs contained in saurian genomes represent a far greater diversity of hepadnaviruses than previously recognized. Through in-depth characterization of eHBV elements, we establish the existence of four distinct subgroups within the genus Avihepadnavirus and trace their evolution through the Cenozoic Era. Furthermore, we provide a completely new perspective on hepadnavirus evolution by showing that the metahepadnaviruses (genus Metahepadnavirus) originated >300 million years ago in the Paleozoic Era and have historically infected a broad range of vertebrates. We also show that eHBVs have been intra-genomically amplified in some saurian lineages, and that eHBVs located at approximately equivalent genomic loci have been acquired in entirely distinct germline integration events. These findings indicate that selective forces have favoured the accumulation of hepadnaviral sequences at specific loci in the saurian germline. Our investigation provides a range of new insights into the long-term evolutionary history of reverse-transcribing DNA viruses and shows that germline incorporation of hepadnaviruses has played a role in shaping the evolution of saurian genomes.
The evolutionary dynamics of endemic human coronaviruses
Authors: Jo Wendy K , Drosten Christian , Drexler Jan Felix
Published: March 2021

Community protective immunity can affect RNA virus evolution by selecting for new antigenic variants on the scale of years, exemplified by the need of annual evaluation of influenza vaccines. The extent to which this process termed antigenic drift affects coronaviruses remains unknown. Alike the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), seasonal human coronaviruses (HCoV) likely emerged from animal reservoirs as new human pathogens in the past. We therefore analyzed the long-term evolutionary dynamics of the ubiquitous HCoV-229E and HCoV-OC43 in comparison with human influenza A virus (IAV) subtype H3N2. We focus on viral glycoprotein genes that mediate viral entry into cells and are major targets of host neutralizing antibody responses. Maximum likelihood and Bayesian phylogenies of publicly available gene datasets representing about three decades of HCoV and IAV evolution showed that all viruses had similar ladder-like tree shapes compatible with antigenic drift, supported by different tree shape statistics. Evolutionary rates inferred in a Bayesian framework were 6.5 × 10−4 (95% highest posterior density (HPD), 5.4–7.5 × 10−4) substitutions per site per year (s/s/y) for HCoV-229E spike (S) genes and 5.7 × 10−4 (95% HPD, 5–6.5 × 10−4) s/s/y for HCoV-OC43 S genes, which were about fourfold lower than the 2.5 × 10−3 (95% HPD, 2.3–2.7 × 10−3) s/s/y rate for IAV hemagglutinin (HA) genes. Coronavirus S genes accumulated about threefold less (P < 0.001) non-synonymous mutations (dN) over time than IAV HA genes. In both IAV and HCoV, the average rate of dN within the receptor binding domains (RBD) was about fivefold higher (P < 0.0001) than in other glycoprotein gene regions. Similarly, most sites showing evidence for positive selection occurred within the RBD (HCoV-229E, 6/14 sites, P < 0.05; HCoV-OC43, 23/38 sites, P < 0.01; IAV, 13/15 sites, P = 0.08). In sum, the evolutionary dynamics of HCoV and IAV showed several similarities, yet amino acid changes potentially representing antigenic drift occurred on a lower scale in endemic HCoV compared to IAV. It seems likely that pandemic SARS-CoV-2 evolution will bear similarities with IAV evolution including accumulation of adaptive changes in the RBD, requiring vaccines to be updated regularly, whereas higher SARS-CoV-2 evolutionary stability resembling endemic HCoV can be expected in the post-pandemic stage.
Multi-transcriptomic analysis points to early organelle dysfunction in human astrocytes in Alzheimer’s disease
Authors: Galea Elena , Weinstock Laura D. , Larramona-Arcas Raquel , Pybus Alyssa F. , Giménez-Llort Lydia , Escartin Carole , Wood Levi B.
Published: March 2021

Recent single-nucleus RNA sequencing of astrocytes in postmortem Alzheimer’s disease (AD) samples is limited by the low number of sequenced astrocytes and small cohort sizes. We developed a systems biology approach to identify astrocytic genes in public large bulk AD transcriptomes. Brain cell specific gene clusters were generated from RNA sequencing data from isolated healthy human brain cells using cell-type enrichment scoring and clustering. Cell-specific gene clusters were localized in whole-brain transcriptomes from 766 subjects diagnosed with AD or mild cognitive impairment (MCI) from the Mount Sinai Hospital, the Mayo Clinic, and the Religious Order Study/Memory and Aging Project (ROSMAP). Gene clusters were organized into manually curated functional categories including astrocytic categories absent from existing platforms, such as perisynaptic astrocytic processes (PAP). Changes among subjects were determined by gene set variation analysis (GSVA) and principal component analysis (PCA). Hierarchical clustering revealed molecular heterogeneity in individuals with the same clinical diagnosis. Particularly in the Mayo Clinic and ROSMAP cohorts, over 50% of Controls presented the massive down-regulation of genes encoding synaptic proteins typical of AD, whereas 30% of AD patients presented Control-like transcriptomic profiles. According to GSVA and PCA, down-regulation of neuronal genes related to synaptic proteins correlated with down-regulation of astrocytic genes encoding mitochondrial and endolysosomal proteins, and up-regulation of genes related to PAP. Transcriptomic data thus unravel a deep phenotypic transformation of human astrocytes in AD, affecting organelles and astrocyte-neuron interactions. We posit that therapies preventing organelle dysfunction in astrocytes may protect neural circuits in preclinical and clinical AD.

Main points

Transcriptomes of control subjects and AD patients segregate in two main molecular profiles regardless of clinical diagnosis.

Dysregulation of the endolysosomal/mitochondrial axis in astrocytes correlates with impaired synaptic plasticity in neurons.
Impact of Vaccine Failure on the Transmission Dynamics of Measles in Nigeria
Authors: Nwankwo Ann , Iboi Enahoro. , Okuonghae Daniel
Published: March 2021

Measles is a vaccine preventable disease. However, it is still a major public health challenge in Nigeria.We therefore formulate a mathematical model for the transmission of measles with a two dose vaccination strategy and weaning of vaccine derived immunity. Using weekly measles cases for Nigeria in 2020 from the Nigeria Center for Disease Control (NCDC), the model was validated. This modelling study via numerical simulations showed that there is a possibility of disease control with a ten fold increase in the vaccination rates. Also, it was shown that primary vaccine failure has more impact on disease dynamics than secondary vaccine failure. Thus control strategies should not just focus on increase the vaccination rates but also look at measures that will help in reducing primary vaccine failure.
Successful incorporation of a genetic risk prediction research platform into routine newborn screening
Authors: Bendor-Samuel Owen M , Wishlade Tabitha , Willis Louise , Aley Parvinder , Choi Edward , Craik Rachel , Mujadidi Yama , Mounce Ginny , Roseman Fenella , De La Horra Gozalo Arancha , Bland James , Taj Nazia , Smith Ian , Ziegler Anette-Gabriele , Bonifacio Ezio , Winkler Christiane , Haupt Florian , Todd John A. , Servais Laurent , Snape Matthew D , Vatish Manu ,   the GPPAD Study Group
Published: March 2021

An increasing number of diseases can be offered treatments that are transformative if administered in a timely manner. However, many of these diseases are currently not included in the newborn screening programs because they lack sensitive and specific metabolic biomarkers, and detection of children at increased risk relies on genetic methods. Type 1 diabetes (T1D) constitutes a potential example of such disease.

Between April 2018 and November 2020, over 15500 babies were enrolled into ‘INGR1D’ (Investigating Genetic Risk for T1D), a research study to identify newborns with an increased genetic risk of T1D. This project, performed as part of a T1D primary prevention study (the Primary Oral Insulin Trial, POInT), has helped to pioneer the integration of genetic screening into the NHS Newborn Blood Spot Screening Programme (NBSSP) for consenting mothers, without affecting the screening pathway. The use of prospective consent to perform personalised genetic testing on samples obtained through the routine NBSSP represents a novel mechanism for clinical genetic research in the UK and provides a model for further population based genetic studies in the newborn.

This project builds on the UK’s role as a world leader in genomic medicine, e.g. through its inception and completion of the 100 000 Genomes Project, and its subsequent ambition to map 5 million further genomes over the next 5 years.

Our aim is therefore to describe the methodology used by INGR1D as a way to demonstrate how a successful research and clinical trial tool can be integrated into a national screening programme, with the potential for the tool to be developed to incorporate multiple diseases with genetic markers without altering the screening pathway.
What is the effect of lockdown upon hospitalisation due to COVID-19 amongst patients from a heart failure registry?
Authors: Essa Hani , Brousas Sophia , Hupptaz Isabel Whybrow , Salmon Thomas , Sankaranarayanan Rajiv
Published: March 2021

Introduction

Coronavirus disease 2019 (COVID-19) is associated with a high risk of mortality especially in patients with cardiovascular conditions such as heart failure. The UK government announced a national lockdown last year to curb the spread of the virus. We conducted this study primarily to ascertain the impact of lockdown upon the incidence of COVID-19 hospitalisation amongst patients with a known diagnosis of heart failure (HF)

Methods

This was a retrospective cohort study of 1097 patients from our HF registry who had presented with acute decompensated HF in 2018 and 2019. Incidence and outcomes of hospitalisation due to COVID-19 were analysed in this cohort both during the 1st UK lockdown as well as after the lockdown period. Co-morbidities, frailty index, clinical features, blood results, and heart failure treatments were compared between the 2 groups (COVID versus no-COVID) and between the group of patients who died versus survivors.

Results

50 out of 801 surviving (6.2%) HF patients required hospitalisation due to COVID-19 from March to November 2020; 24 patients (3.1%) during the first lockdown and 26 (3.5%) in the post-lockdown period; p=0.7. In comparison to patients not hospitalised with COVID-19 (“no-COVID group), there was a significantly higher prevalence of co-morbidities amongst HF patients who were hospitalised with COVID-19, such as hypertension (p<0.001), diabetes (p=0.005), ischaemic heart disease (p=0.01) and increased body mass index. 30 day mortality amongst HF patients hospitalised due to COVID-19 was 52%. Rockwood Frailty Score ≥6 (OR 6.530695 % CI:1.8958 to 22.4961; p=0.003) and diabetes (OR 3.82;95% CI 1.13 to 12.95; p=0.03) were independent predictors of 30 day mortality.

Conclusion

Our data suggests that the incidence of hospitalisation due to COVID-19 was similar both during as well as post lockdown amongst patients from our HF registry. HF patients with cardiovascular co-morbidities such as obesity, hypertension, diabetes and ischaemic heart disease have a higher risk of hospitalisation due to COVID-19. Diabetes and Rockwood Frailty score are independent predictors of short term mortality. Co-morbidity and frailty scores should be incorporated during initial assessment to help risk-prediction.
The impact of varying class sizes on epidemic spread in a university population
Authors: Best Alex , Singh Prerna , Ward Charlotte , Vitale Caterina , Oliver Megan , Idris Laminu , Poulston Alison
Published: March 2021

A common non-pharmaceutical intervention (NPI) during the Covid-19 pandemic has been group size limits. Further, educational settings of schools and universities have either fully closed or reduced their class sizes. As countries begin to reopen classrooms, a key question will be how large classes can be while still preventing local outbreaks of disease. Here we develop and analyse a simple, stochastic epidemiological model where individuals (considered as students) live in fixed households and are assigned to a fixed class for daily lessons. We compare key measures of the epidemic - the peak infected, the total infected by day 180 and the calculatedR0- as the size of class is varied. We find that class sizes of 10 could largely restrict outbreaks and often had overlapping inter-quartile ranges with our most cautious case of classes of 5. However, class sizes of 30 or more often result in large epidemics. Reducing the class size from 40 to 10 can reduceR0by over 30%, as well as signficantly reducing the numbers infected. Intermediate class sizes show considerable variation, with the total infected varying by as much as from 10% to 80% for the same class size. We show that additional in-class NPIs can limit the epidemic still further, but that reducing class sizes appears to have a larger effect on the epidemic. We do not specifically tailor our model for Covid-19, but our results stress the importance of small class sizes for preventing large outbreaks of infectious disease.
Early medical abortion by telemedicine in the United Kingdom: A cost-effectiveness analysis
Authors: Hawkins James E , Glasier Anna , Hall Stephen , Regan Lesley ,   Homerton University Hospital Foundation Trust,   University Hospitals Bristol NHS Foundation Trust,   Aneurin Bevan University Health Board
Published: March 2021

Objective

To determine the potential cost savings resulting from the introduction of routine early medical abortion at home by telemedicine in the United Kingdom.

Design

A cost-effectiveness analysis Setting: United Kingdom

Population

Women in 2020 undergoing early medical abortion provided by three independent abortion providers and two NHS abortion clinics.

Methods

Computation of the costs of each abortion procedure and of managing failed or incomplete abortion and haemorrhage requiring blood transfusion.

Outcome measures

Cost savings

Results

Overall estimated cost savings are £15.80 per abortion undertaken by independent abortion providers representing a saving to the NHS of over £3 million per year. Limited data from NHS services resulted in an estimated average saving of £188.84 per abortion.

Conclusions

Were telemedicine EMA to become routine, an increase in the number of women eligible for medical rather than surgical abortion, and a reduction in adverse events resulting from earlier abortion could result in significant cost-savings.

Tweetable Abstract

Early medical abortion at home using telemedicine could save the NHS £3 million per year
Nationwide rollout reveals efficacy of epidemic control through digital contact tracing
Authors: Elmokashfi Ahmed , Sundnes Joakim , Kvalbein Amund , Naumova Valeriya , Reinemo Sven-Arne , Florvaag Per Magne , Stensland Håkon Kvale , Lysne Olav
Published: March 2021

Fueled by epidemiological studies of SARS-CoV-2, contact tracing by mobile phones has been put to use in many countries. A year into the pandemic, we lack conclusive evidence on its effectiveness. Here, we used a unique real world contact data set, collected during the rollout of the first Norwegian contact tracing app in the Spring of 2020, to address this gap. Our dataset involves millions of contacts between 12.5% of the adult population, and enabled us to measure the real-world app performance. The technological tracing efficacy was measured at 80%, and we estimated that at least 11.0% of the discovered close contacts could not be identified by manual contact tracing. The overall effectiveness of digital tracing depends strongly on app uptake, but significant impact can be achieved for moderate uptake numbers. Used as a supplement to manual tracing and other measures, digital tracing can be instrumental in controlling the pandemic. Our findings can thus help informing public health policies in the coming months.
Development of the foregut inKatharina tunicata(Mollusca; Polyplacophora)
Authors: Biggar Brandy S.
Published: March 2021

As a highly diverse phyla, Mollusca is both intriguing to study and difficult to define. No single common feature distinguishes the phyla, but the most common and recognizable is the radula. Throughout Molluscan history, there have been many developments to the radular structure. Evolutionary development of unique radular structures may have been made possible by developmental modularity. This histological study examines the development of polyplacophoran internal gut development. Here, I describe the developmental sequence of chiton feeding structures for the first time. Feeding structures are present by 10 days post hatch. Future research should examine larval stages prior to this in order to determine whether developmental modularity exists in polyplacophorans.