bluuebunny/crossref_metadata_2025 huggingface dataset:
Novel Algorithm for Image Classification Using Cross Deep Learning Technique
Authors: Kumar Jugnesh , Bedi Pradeep , Goyal S B , Shrivastava Ashish , Kumar Sunil
Published: March 2021

The basic concepts of training and the model structure of deep belief networks (DBNs) in deep analysis are studied to apply image recognition in the area of deep learning. Random propound is provided with the parameter in the fine-tuning stage and the randomly hidden layer eliminated to maintain unchanged weights. The results show that the layered DBN training system reduces training problems and training times significantly. In the small sample, the deep faith network has improved significantly after introducing the down sample and random dropdown and effectively alleviates the over-fitting phenomenon. Design a new Deep Learning Image Recognition and Classification Algorithm. Novel Algorithm for Image Classification Using Cross Deep Learning Technique.
A Design Approach for Identifying, Diagnosing and Controlling Soybean Diseases using CNN Based Computer Vision of the Leaves for Optimizing the Production
Authors: Kamal Raj , Tiwari Sadhna , Kolhe Savita , Deshpande Manojkumar Vilasrao
Published: March 2021

Leaves express the initial symptoms of many diseases in soybean crop. CNN based Computer-Vision (CV) of the leaf-images identifies, enables the diagnosing and controlling the soybean-crop diseases. All three actions need proactive maintenance and Operational Intelligence (OI) for the model used for the control measures. The OI optimizes production. The paper describes a new design approach. Proposed design deploys Computer-Vision (CV), Convolution Neural Network (CNN), Edge AI Computing and the IoT. The approach consists of four-stage framework. Four stages are (1) Cameras in a chain of two sets of four cameras, each at two plants. (2) Edge-AI computing unit for each pair of plants at the field. (3) Edge-Server, which serves multiple networked edge units, one each of the two, sets of cameras. The server also functions as gateway for Internet connectivity with Cloud services. (4) Cloud services for the OI, proactively control the updating CNN model feature metrics, CV functions and camera operations.
Fake News Detection Using Machine Learning Approaches
Authors: Khanam Z , Alwasel B N , Sirafi H , Rashid M
Published: March 2021

The fake news on social media and various other media is wide spreading and is a matter of serious concern due to its ability to cause a lot of social and national damage with destructive impacts. A lot of research is already focused on detecting it. This paper makes an analysis of the research related to fake news detection and explores the traditional machine learning models to choose the best, in order to create a model of a product with supervised machine learning algorithm, that can classify fake news as true or false, by using tools like python scikit-learn, NLP for textual analysis. This process will result in feature extraction and vectorization; we propose using Python scikit-learn library to perform tokenization and feature extraction of text data, because this library contains useful tools like Count Vectorizer and Tiff Vectorizer. Then, we will perform feature selection methods, to experiment and choose the best fit features to obtain the highest precision, according to confusion matrix results.
Fitness for Solving SMCP Using Evolutionary Algorithm
Authors: Gupta Neetu , Rana Ajay , Gupta Sumit
Published: March 2021

Search based software engineering is a paradigm with prime focus to apply search techniques and meta-heuristics for solving various software engineering open NP hard problems. Evolutionary meta-heuristics techniques are already proven to provide optimized solutions to other software engineering problems like automated software test data generation, project estimation, class responsibility assignment to name few. Software module clustering is such an open problem of software engineering that cannot be solved in definite manner. For a given module dependency graph of software system, there exists large number of possible partitions. Identifying a good partition to cluster all modules of software system is an exhaustive search that cannot be carried out in finite manner. With search based techniques applying evolutionary algorithms, an optimized solution can be identified with evaluating goodness of a given partitions. Identifying a fitness function that can direct the search towards optimal solution is very critical. This paper discusses various types of fitness applicable to solve software module clustering problem.
A Review on Swarm Intelligence Techniques in Automated Cryptanalysis of Classical Substitution Cipher
Authors: Jain Ashish , Vishwakarma Santosh Kumar , Sharma Prakash Chandra , Gupta Nirmal Kumar
Published: March 2021

Between the year 2006 and 2019, a considerable new and different swarm intelligence techniques have been presented in the literature for automated cryptanalysis of classical substitution cipher. This paper compares the performance of these new and different swarm intelligence techniques. Three main comparison measures are considered to assess the performance of presented swarm intelligence techniques: efficiency, effectiveness, and success rate. To the best of author knowledge first time this kind of review has been carried out. It is noteworthy that among the presented swarm intelligence techniques the performance of cuckoo search technique is best with respect to all the measures.
Energy Efficient WSN Clustering Using Cuckoo Search
Authors: Bhatt Devershi Pallavi , Sharma Yogesh Kumar , Sharma Anand
Published: March 2021

A comprehensive range of applications exists for Wireless Sensor Networks (WSNs) have in today’s world. To name a few they are used in monitoring environmental parameters, condition of infrastructures, and related geophysical processes near to real-time, water quality monitoring, air pollution monitoring, etc. Wireless sensors can be placed in places that are difficult to human intervention for impossible to reach with a physical wired system. These WSNs, are low in power and computation so constructing an energy-effective data collecting protocol is a demanding issue. This is because all sensor nodes are usually provided with limited power sources. The development of an energy-efficient algorithm is the need of the hour as replacing the energy sources for the sensor nodes is a tedious task. Various clustering protocols have been proposed earlier but they suffer unbalanced energy problems and are not efficient enough to cater to the needs of these WSNs. To deal with this challenge, an improved algorithm using cuckoo-based search clustering protocol has been proposed in this research paper.
A Critical Review on Nature Inspired Optimization Algorithms
Authors: Soni Vishnu , Sharma Abhay , Singh Vijander
Published: March 2021

Nature-inspired optimization algorithms turned out to be progressively more accepted in modern era, and the majority of these meta-heuristic algorithms, such as ‘Bat algorithm’, ‘Lion Algorithm’, ‘Particle swarm optimization’, ‘Water wave optimization algorithm’, ‘Elephant herding optimization algorithm’, ‘Optics inspired optimization algorithm’, ‘Cuckoo search’, ‘Flower algorithms’, ‘Genetic algorithms’, ‘Differential evolution’, ‘Harmony search’, ‘Simulated annealing’, and many more. This paper attempts to establish the most recent improvements concerning all main ‘Nature-Inspired Algorithms’ and it is strived to coat at least one hottest optimization problem related to these above-mentioned algorithms. Based on their outcomes it is established that there are a few considerable gaps between hypothesis and observe. On one side, nature-inspired algorithms for optimization are extremely successful and can acquire most favourable clarifications in a convincingly realistic time. On the other side, mathematical investigation of key characteristics of these algorithms is missing. It is extremely advantageous that researchers add on some impending into the neutrality of diverse nature-inspired algorithms and hence can obtain the dare to crack key difficulties that must be solved. The paper is extending extensively and intensifying the need to evaluate and review these various optimization algorithms. This paper is organized in a manner to provide complete description of each NIA starting from introduction then review of literature, analysis of various NIAs and finally conclusion.
Digital Transformation Trends and Innovation
Authors: Guarda Teresa , Balseca Joel , García Kevin , González Jairon , Yagual Fabian , Castillo-Beltran Hernán
Published: March 2021

Today, advances in technology bring changes to people’s lifestyles, and challenging organizations to accompany these advances. Organizational managers and those responsible for the Information Technology (IT) department must evaluate current trends in innovation, and determine how they can boost business, creating new business models, and promoting competitiveness. The objective of these paper is presented a group of technological advances aimed at being the latest digital trends and changing previous trends by producing improvements or updates, the same ones that streamline processes in the field of business intelligence (BI). In this survey paper, current trends in the Internet of Things (IoT) are described, as well as topics related to 5G mobile communication, WiFi 6 technologies, the transformation of the user’s technological experience, and Machine Learning (ML). In addition, the support in decision-making process will be analysed as these trends, both personally and at the business level.
Linear constrained combinatorial optimization on well-described sets
Authors: Pichugina Oksana , Koliechkina Liudmyla
Published: March 2021

A Horizontal method (LCCO-HM) for linear constrained combinatorial optimization (LCCO) on well-described combinatorial sets (CWDs) is offered. LCCO-HM utilizes an essential feature of the sets to solve linear unconstraint programs in polynomial time. The method belongs to the Branch and Bound group. It reduces a search domain to solutions of auxiliary unconstrained combinatorial problems and performs pruning branches based on properties of a linear function on CWDs. Applicability of LCCO-HM is justified for sets of multipermutations and partial multipermutations embedded in Euclidean space. LCCO-HM is illustrated by an example of solving a permutation-based linear optimization problem.
An Empirical Study on Lean Performance Parameters of Manufacturing Sector
Authors: Vijayvargy Lokesh , Gupta Srikant
Published: March 2021

Growth and GDP of any nation is depend on its in-house manufacturing capacity. Due to manufacturing many countries like: China, Japan, USA, and Korea are leading world in growth and employability. But due to low cost and govt. policy, India is one of the most lucrative option for manufacturing industry to prosper. This paper will help us in identification of lean performance parameters of manufacturing companies in India. Data were collected in form of questionnaire by mangers of 100 manufacturing firms to identify various lean performance parameters. Sample of manufacturing industry are like agriculture tools and equipment’s, Material handling equipment’s, Parts of various machines parts and construction machines and parts, bolts and nuts, etc are included in our research. The respondent has different position in organization like HR manager, operations manager, SCM manager, owner, director, etc. To identify parameters of lean performance, this study used statistical tools. The outcomes of the research work offer the important implications for the Indian manufacturing organizations to understand the factors affecting their performance.
A Preservation Technology Model for Deteriorating Items with Advertisement Dependent Demand and Partial Trade Credit
Authors: Rathore Himanshu , Sharma Rohit Shiv Ashish
Published: March 2021

This study presents a preservation technology model for deteriorating items with constant rate of deterioration. The requirements for the items are received as a function of advertisement frequency and selling price. The two types of trade credit is the main focus of this study. First one is provided by the supplier to the retailer and another one is the partial trade credit offered by the retailer to the customer. The optimal policy is presented to earn maximum profit with optimal values of selling price, advertisement frequency, preservation technology and total cycle length. The study is numerically verified with sensitivity analysis to check the sensitivity of the model.
Comparison of Pairwise Similarity Distance Methods for Effective Hashing
Authors: Öztürk Ş
Published: March 2021

Content-based image retrieval (CBIR) methods search for points with the most similar content to query features from within a large dataset. The most notable approach for this purpose is an approximate nearest neighbor (ANN) searching. The main properties expected from a retrieval system can be listed as follows; low storage requirement, high retrieve speed, and high average precision. Hashing, which can generate discriminative and low-dimensional binary codes, is one of today’s most effective ANN searching methods. Although there are various hashing approaches in the literature, almost all hashing approaches consist of low-dimension feature representation and binarization sections. This study focuses on the low-dimension feature representation. Hand-crafted or deep learning based approaches are used for feature extraction in hashing methods. These features are the main components that affect the performance in creating binary codes. Contrastive loss is often used in the literature to update the learnable parameters of these feature extraction algorithms. The distance parameter of these data points critical to calculating contrastive loss. In this study, contrastive loss performance is tested using five different distance methods (Euclidean, Manhattan, Cosine, Minkowski, Chebyshev) for more effective feature representation. Retrieval performance is tested using low-dimensional feature vectors produced by these methods in MNIST and CIFAR-10 datasets. It is thought that the information obtained from this study is very useful for new researchers.
Talk about Pop Muzik: Discussion of Enrico Terrone, ‘Listening to Other Minds: A Phenomenology of Pop Songs’,BJA60 (2020), 435–453
Authors: Wiltsher Nick
Published: March 2021

In ‘Listening to Other Minds’, Enrico Terrone provides an account of the mental activity in which we ought to engage to appreciate pop music. He argues that we should ‘play a game of make-believe’ (p. 452) in which we imagine that we can ‘hear … the mind’ of a fictional character (pp. 452, 440). We should use this ability to grasp the thoughts and feelings that the mind contains, and thus undertake ‘exploration’ of the character’s ‘inner life’ (p. 445). This article argues, first, that only a simplified version of the account is plausible; second, that its plausibility as a general account of pop music depends on a dubious conception of the ‘paradigm cases’ (p. 449); third, that its desirability as an account of a narrower range of cases is questionable; and, fourth, that it is motivated by unsuitable assumptions about representation in pop.
Structure-based drug repurposing against COVID-19 and emerging infectious diseases: methods, resources and discoveries
Authors: Masoudi-Sobhanzadeh Yosef , Salemi Aysan , Pourseif Mohammad M , Jafari Behzad , Omidi Yadollah , Masoudi-Nejad Ali
Published: March 2021

To attain promising pharmacotherapies, researchers have applied drug repurposing (DR) techniques to discover the candidate medicines to combat the coronavirus disease 2019 (COVID-19) outbreak. Although many DR approaches have been introduced for treating different diseases, only structure-based DR (SBDR) methods can be employed as the first therapeutic option against the COVID-19 pandemic because they rely on the rudimentary information about the diseases such as the sequence of the severe acute respiratory syndrome coronavirus 2 genome. Hence, to try out new treatments for the disease, the first attempts have been made based on the SBDR methods which seem to be among the proper choices for discovering the potential medications against the emerging and re-emerging infectious diseases. Given the importance of SBDR approaches, in the present review, well-known SBDR methods are summarized, and their merits are investigated. Then, the databases and software applications, utilized for repurposing the drugs against COVID-19, are introduced. Besides, the identified drugs are categorized based on their targets. Finally, a comparison is made between the SBDR approaches and other DR methods, and some possible future directions are proposed.
Multiscale part mutual information for quantifying nonlinear direct associations in networks
Authors: Shang Junliang , Wang Jing , Sun Yan , Li Feng , Liu Jin-Xing , Zhang Honghai
Published: March 2021

Motivation

For network-assisted analysis, which has become a popular method of data mining, network construction is a crucial task. Network construction relies on the accurate quantification of direct associations among variables. The existence of multiscale associations among variables presents several quantification challenges, especially when quantifying nonlinear direct interactions.

Results

In this study, the multiscale part mutual information (MPMI), based on part mutual information (PMI) and nonlinear partial association (NPA), was developed for effectively quantifying nonlinear direct associations among variables in networks with multiscale associations. First, we defined the MPMI in theory and derived its five important properties. Second, an experiment in a three-node network was carried out to numerically estimate its quantification ability under two cases of strong associations. Third, experiments of the MPMI and comparisons with the PMI, NPA and conditional mutual information were performed on simulated datasets and on datasets from DREAM challenge project. Finally, the MPMI was applied to real datasets of glioblastoma and lung adenocarcinoma to validate its effectiveness. Results showed that the MPMI is an effective alternative measure for quantifying nonlinear direct associations in networks, especially those with multiscale associations.

Availability and implementation

The source code of MPMI is available online at https://github.com/CDMB-lab/MPMI.

Supplementary information

Supplementary data are available at Bioinformatics online.
Brain size evolution in whales and dolphins: new data from fossil mysticetes
Authors: Mccurry Matthew R , Marx Felix G , Evans Alistair R , Park Travis , Pyenson Nicholas D , Kohno Naoki , Castiglione Silvia , Fitzgerald Erich M G
Published: March 2021

Cetaceans (whales and dolphins) have some of the largest and most complex brains in the animal kingdom. When and why this trait evolved remains controversial, with proposed drivers ranging from echolocation to foraging complexity and high-level sociality. This uncertainty partially reflects a lack of data on extinct baleen whales (mysticetes), which has obscured deep-time patterns of brain size evolution in non-echolocating cetaceans. Building on new measurements from mysticete fossils, we show that the evolution of large brains preceded that of echolocation, and subsequently followed a complex trajectory involving several independent increases (e.g. in rorquals and oceanic dolphins) and decreases (e.g. in right whales and ‘river dolphins’). Echolocating whales show a greater tendency towards large brain size, thus reaffirming cognitive demands associated with sound processing as a plausible driver of cetacean encephalization. Nevertheless, our results suggest that other factors such as sociality were also important.
Activation of the basal ganglia and indirect pathway neurons during frontal lobe seizures
Authors: Brodovskaya Anastasia , Shiono Shinnosuke , Kapur Jaideep
Published: March 2021

There are no detailed descriptions of neuronal circuit active during frontal lobe motor seizures. Using activity reporter mice, local field potential recordings, tissue clearing, viral tracing, and super-resolution microscopy, we found neuronal activation after focal motor to bilateral tonic-clonic seizures in the striatum, globus pallidus externus, subthalamic nucleus, substantia nigra pars reticulata and neurons of the indirect pathway. Seizures preferentially activated dopamine D2 receptor-expressing neurons over D1 in the striatum, which have different projections. Furthermore, the D2 receptor agonist infused into the striatum exerted an anticonvulsant effect. Seizures activate structures via short and long latency loops, and anatomical connections of the seizure focus determine the seizure circuit. These studies, for the first time, show activation of neurons in the striatum, globus pallidus, subthalamic nucleus, and substantia nigra during frontal lobe motor seizures on the cellular level, revealing a complex neuronal activation circuit subject to modulation by the basal ganglia.
Severe hypercalcaemia early after kidney transplantation in two patients with severe secondary hyperparathyroidism previously treated with etelcalcetide
Authors: Dachy Guillaume , Pochet Jean-Michel , Labriola Laura , Buemi Antoine , Gillion Valentine , Jadoul Michel , Kanaan Nada , Devresse Arnaud
Published: March 2021

Cinacalcet and, more recently, etelcalcetide revolutionized the treatment of chronic kidney disease–mineral and bone disorder (CKD–MBD). Kidney transplant (KT) usually improves CKD–MBD. However, a significant proportion of KT recipients have high serum calcium levels, not requiring any treatment. We report two patients previously treated with etelcalcetide who developed severe (>3.3 mmol/L) hypercalcaemia in the early post-KT course, requiring parathyroidectomy. Pathological studies showed parathyroid adenomas and hyperplasia. One patient had a graft biopsy showing numerous intratubular calcium phosphate crystals. These observations should prompt pharmacovigilance studies and careful follow-up of KT recipients previously treated with etelcalcetide.
Hormonal modulation of reproduction and fertility signaling in polistine wasps
Authors: Oi Cintia Akemi , da Silva Rafael Carvalho , Stevens Ian , Ferreira Helena Mendes , Nascimento Fabio Santos , Wenseleers Tom
Published: March 2021

In social insects, it has been suggested that reproduction and the production of particular fertility-linked cuticular hydrocarbons (CHC) may be under shared juvenile hormone (JH) control, and this could have been key in predisposing such cues to later evolve into full-fledged queen pheromone signals. However, to date, only few studies have experimentally tested this “hormonal pleiotropy” hypothesis. Here, we formally test this hypothesis using data from four species of Polistine wasps, Polistes dominula, Polistes satan, Mischocyttarus metathoracicus, and Mischocyttarus cassununga, and experimental treatments with JH using the JH analogue methoprene and the anti-JH precocene. In line with reproduction being under JH control, our results show that across these four species, precocene significantly decreased ovary development when compared with both the acetone solvent-only control and the methoprene treatment. Consistent with the hormonal pleiotropy hypothesis, these effects on reproduction were further matched by subtle shifts in the CHC profiles, with univariate analyses showing that in P. dominula and P. satan the abundance of particular linear alkanes and mono-methylated alkanes were affected by ovary development and our hormonal treatments. The results indicate that in primitively eusocial wasps, and particularly in Polistes, reproduction and the production of some CHC cues are under joint JH control. We suggest that pleiotropic links between reproduction and the production of such hydrocarbon cues have been key enablers for the origin of true fertility and queen signals in more derived, advanced eusocial insects.
Myocardial infarction secondary to coronary embolus in a patient with left ventricular non-compaction cardiomyopathy: a case report
Authors: Dhawan Rahul , Kadir Sajid , Barton David E , Stone Jeremy R , Chatzizisis Yiannis S
Published: March 2021

Background

Coronary embolism is a rare cause of myocardial infarction (MI). We present a case report which emphasizes the importance of intracoronary imaging in these cases to identify the pathophysiological mechanism of MI.

Case summary

A 53-year-old male with no past medical history presented to the hospital with typical angina. Electrocardiogram and serum troponin I level trend confirmed non-ST-elevation myocardial infarction. Coronary angiography showed no evidence of any obstructive coronary artery disease, but two small thrombi were noted in the distal first obtuse marginal branch. Optical coherence tomography imaging confirmed this finding in absence of any underlying atherosclerotic plaque rupture or erosion. Cardiac magnetic resonance imaging revealed the diagnosis of non-compaction cardiomyopathy with severely depressed left ventricular function. Transmural MI was revealed by late gadolinium enhancement in the mid-lateral wall. Based on the pathophysiology of the MI confirmed by intracoronary imaging, antiplatelet medications were discontinued, and the patient was discharged on warfarin. Medical therapy was initiated for his cardiomyopathy. The patient recovered well and was asymptomatic at 1-year follow-up visit.

Discussion

Intracoronary imaging plays an important role to supplement coronary angiography to confirm the pathophysiology of MI in coronary embolism cases. This is important as it alters management in these patients.
The association between cardiovascular disease admission rates and the coronavirus disease 2019 lockdown and reopening of a nation: a Danish nationwide cohort study
Authors: Butt Jawad H , Østergaard Lauge , Gerds Thomas A , Lauridsen Marie D , Kragholm Kristian , Schou Morten , Phelps Matthew , Gislason Gunnar H , Torp-Pedersen Christian , Køber Lars , Fosbøl Emil L
Published: March 2021

Aims

To investigate the admission rates of cardiovascular diseases, overall and according to subgroups, and subsequent mortality rates during the coronavirus disease 2019 societal lockdown (12 March 2020) and reopening phase (15 April 2020) in Denmark.

Methods and results

Using Danish nationwide registries, we identified patients with a first-time acute cardiovascular admission in two periods: (i) 2 January–16 October 2019 and (ii) 2 January–15 October 2020. Weekly incidence rates of a first-time cardiovascular admission, overall and according to subtypes, in the two periods were calculated. The incidence rate of first-time cardiovascular admissions overall was significantly lower during the first weeks of lockdown in 2020 compared with a similar period in 2019 but increased after the gradual reopening of the Danish society. A similar trend was observed for all subgroups of cardiovascular diseases. The mortality rate among patients admitted after March 12 was not significantly different in 2020 compared with 2019 [mortality rate ratio 0.98; 95% confidence interval (CI) 0.91–1.06)].

Conclusion

In Denmark, we observed a substantial decrease in the rate of acute cardiovascular admissions, overall and according to subtypes, during the first weeks of lockdown. However, after the gradual reopening of the Danish society, the admission rates for acute cardiovascular diseases increased and returned to rates similar to those observed in 2019. The mortality rate in patients admitted with cardiovascular diseases during lockdown was similar to that of patients during the same period in 2019.
Older Adults Demonstrate Biomarker Evidence of the Persistent Inflammation, Immunosuppression, and Catabolism Syndrome (PICS) After Sepsis
Authors: Mankowski Robert T , Anton Stephen D , Ghita Gabriela L , Brumback Babette , Darden Dijoia B , Bihorac Azra , Leeuwenburgh Christiaan , Moldawer Lyle L , Efron Philip A , Brakenridge Scott C , Moore Frederick A
Published: March 2021

Background

Hospital deaths after sepsis have decreased substantially and most young adult survivors rapidly recover (RAP). However, many older survivors develop chronic critical illness (CCI) with poor long-term outcomes. The etiology of CCI is multifactorial and the relative importance remains unclear. Sepsis is caused by a dysregulated immune response and biomarkers reflecting a persistent inflammation, immunosuppression, and catabolism syndrome (PICS) have been observed in CCI after sepsis. Therefore, the purpose of this study was to compare serial PICS biomarkers in (i) older (vs young) adults and (ii) older CCI (vs older RAP) patients to gain insight into underlying pathobiology of CCI in older adults.

Method

Prospective longitudinal study with young (≤45 years) and older (≥65 years) septic adults, who were characterized by (i) baseline predisposition, (ii) hospital outcomes, (iii) serial Sequential Organ Failure Assessment (SOFA) organ dysfunction scores over 14 days, (iv) Zubrod Performance status at 3-, 6-, and 12-month follow-up, and (v) mortality over 12 months, was conducted. Serial blood samples over 14 days were analyzed for selected biomarkers reflecting PICS.

Results

Compared to the young, more older adults developed CCI (20% vs 42%) and had markedly worse serial SOFA scores, performance status, and mortality over 12 months. Additionally, older (vs young) and older CCI (vs older RAP) patients had more persistent aberrations in biomarkers reflecting inflammation, immunosuppression, stress metabolism, lack of anabolism, and antiangiogenesis over 14 days after sepsis.

Conclusion

Older (vs young) and older CCI (vs older RAP) patient subgroups demonstrate early biomarker evidence of the underlying pathobiology of PICS.
Frailty, With or Without Cognitive Impairment, Is a Strong Predictor of Recurrent Falls in a US Population-Representative Sample of Older Adults
Authors: Ge Mei-Ling , Simonsick Eleanor M , Dong Bi-Rong , Kasper Judith D , Xue Qian-Li
Published: March 2021

Background

Physical frailty and cognitive impairment have been separately associated with falls. The purpose of the study is to examine the associations of physical frailty and cognitive impairment separately and jointly with incident recurrent falls among older adults.

Methods

The analysis included 6000 older adults in community or non-nursing home residential care settings who were at least 65 years old and participated in the National Health and Aging Trends Study. Frailty was assessed using the physical frailty phenotype; cognitive impairment was defined by bottom quintile of the clock-drawing test or immediate and delayed 10-word recall, or self/proxy-report of diagnosis of dementia, or AD8 score at least 2. The marginal means/rates models were used to analyze the associations of frailty and cognitive impairment with recurrent falls over 6 years of follow-up between 2011 and 2017.

Results

Of the 6000 older adults, 1787 (29.8%) had cognitive impairment only, 334 (5.6%) had frailty only, 615 (10.3%) had both, and 3264 (54.4%) had neither. After adjusting for age, sex, race, education, living alone, obesity, disease burden, and mobility disability, those with frailty (with or without cognitive impairment) at baseline had higher rates of recurrent falls than those without cognitive impairment and frailty (frailty only: rate ratio [RR] = 1.31, 95% confidence interval [CI] = 1.18–1.44; both: RR = 1.28, 95% CI = 1.17–1.40). The association was marginally significant for those with cognitive impairment only (RR = 1.07, 95% CI = 1.00–1.13).

Conclusions

Frailty and cognitive impairment were independently associated with recurrent falls in noninstitutionalized older adults. There was a lack of synergistic effect between frailty and cognitive impairment.
Chromosome-level genome assemblies of the malaria vectors Anopheles coluzzii and Anopheles arabiensis
Authors: Zamyatin Anton , Avdeyev Pavel , Liang Jiangtao , Sharma Atashi , Chen Chujia , Lukyanchikova Varvara , Alexeev Nikita , Tu Zhijian , Alekseyev Max A , Sharakhov Igor V
Published: March 2021

Background

Anopheles coluzzii and Anopheles arabiensis belong to the Anopheles gambiae complex and are among the major malaria vectors in sub-Saharan Africa. However, chromosome-level reference genome assemblies are still lacking for these medically important mosquito species.

Findings

In this study, we produced de novo chromosome-level genome assemblies for A. coluzzii and A. arabiensis using the long-read Oxford Nanopore sequencing technology and the Hi-C scaffolding approach. We obtained 273.4 and 256.8 Mb of the total assemblies for A. coluzzii and A. arabiensis, respectively. Each assembly consists of 3 chromosome-scale scaffolds (X, 2, 3), complete mitochondrion, and unordered contigs identified as autosomal pericentromeric DNA, X pericentromeric DNA, and Y sequences. Comparison of these assemblies with the existing assemblies for these species demonstrated that we obtained improved reference-quality genomes. The new assemblies allowed us to identify genomic coordinates for the breakpoint regions of fixed and polymorphic chromosomal inversions in A. coluzzii and A. arabiensis.

Conclusion

The new chromosome-level assemblies will facilitate functional and population genomic studies in A. coluzzii and A. arabiensis. The presented assembly pipeline will accelerate progress toward creating high-quality genome references for other disease vectors.
The role of religion in mitigating the COVID-19 pandemic: the Malaysian multi-faith perspectives
Authors: Tan Min Min , Musa Ahmad Farouk , Su Tin Tin
Published: March 2021

Social distancing is crucial in breaking the cycle of transmission of COVID-19. However, many religions require the faithful to congregate. In Malaysia, the number of COVID-19 cases spiked up from below 30 in February 2020 to more than a thousand a month later. The sudden increase was mostly linked to a large Islamic gathering attended by 16,000 near the capital, Kuala Lumpur. Another large COVID-19 cluster was from a church gathering in Kuching, Sarawak. Within a few weeks, Malaysia became the worst hit country by COVID-19 in Southeast Asia. While religious leaders have advised social distancing among their congregants, the belief that “God is our shield” is often cited for gathering. There is a need to promote sound decision-making among religious adherents so that they will not prioritize their loyalty to the subjective interpretation of religion over evidence-based medicine. Malaysia, a multi-cultural and multi-faith country, is an example of how religious beliefs could strongly influence health behaviours at individual and community levels. In this article, we detail the religious aspects of COVID-19 prevention and control in Malaysia and discuss the possible role of religious organizations in encouraging sound decision-making among religious adherents in mitigating this crisis. We make recommendations on how to promote a partnership between the healthcare system and religious organizations, and how religion and faith could be integrated into health promotion channels and resources in the response of COVID-19 and future communicable diseases.
The Arab Court of Human Rights and the Enforcement of the Arab Charter on Human Rights
Authors: Almutawa Ahmed
Published: March 2021

Under the League of Arab States’ human rights regime, Arab countries are governed by the Arab Charter of Human Rights 2004. The Charter, however, lacks an enforcement mechanism. The Statute of the Arab Court of Human Rights 2014 aims to fill this enforcement void. This article addresses the criticism that, because it fails to provide for a direct right of individual petition, the Statute is not fit for purpose. It is argued contrarily that, within the context of an Arab human rights system, the Court should be welcomed as an important step in the process of establishing an effective regime.
HOSTED—England’s Household Transmission Evaluation Dataset: preliminary findings from a novel passive surveillance system of COVID-19
Authors: Hall JA , Harris RJ , Zaidi A , Woodhall SC , Dabrera G , Dunbar JK
Published: March 2021

Background

 Household transmission of SARS-CoV-2 is an important component of the community spread of the pandemic. Little is known about the factors associated with household transmission, at the level of the case, contact or household, or how these have varied over the course of the pandemic.

Methods

 The Household Transmission Evaluation Dataset (HOSTED) is a passive surveillance system linking laboratory-confirmed COVID-19 cases to individuals living in the same household in England. We explored the risk of household transmission according to: age of case and contact, sex, region, deprivation, month and household composition between April and September 2020, building a multivariate model.

Results

 In the period studied, on average, 5.5% of household contacts in England were diagnosed as cases. Household transmission was most common between adult cases and contacts of a similar age. There was some evidence of lower transmission rates to under-16s [adjusted odds ratios (aOR) 0.70, 95% confidence interval (CI) 0.66–0.74). There were clear regional differences, with higher rates of household transmission in the north of England and the Midlands. Less deprived areas had a lower risk of household transmission. After controlling for region, there was no effect of deprivation, but houses of multiple occupancy had lower rates of household transmission [aOR 0.74 (0.66–0.83)].

Conclusions

 Children are less likely to acquire SARS-CoV-2 via household transmission, and consequently there was no difference in the risk of transmission in households with children. Households in which cases could isolate effectively, such as houses of multiple occupancy, had lower rates of household transmission. Policies to support the effective isolation of cases from their household contacts could lower the level of household transmission.
A novel osimertinib-resistant human lung adenocarcinoma cell line harbouring mutant EGFR and activated IGF1R
Authors: Makimoto Go , Ninomiya Kiichiro , Kubo Toshio , Sunami Ryota , Kato Yuka , Ichihara Eiki , Ohashi Kadoaki , Rai Kammei , Hotta Katsuyuki , Tabata Masahiro , Maeda Yoshinobu , Kiura Katsuyuki
Published: March 2021

Objective

A third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI), osimertinib, is the standard treatment for patients with non-small cell lung cancer harbouring mutant EGFR. Unfortunately, these patients inevitably acquire resistance to EGFR-TKI therapies, including osimertinib. However, the mechanism associated with this resistance remains unclear.

Methods

A 63-year-old Japanese female with lung adenocarcinoma underwent right upper lobectomy (pT1bN2M0 pStage IIIA, EGFR Ex21 L858R). She manifested post-operative tumour recurrence with multiple lung metastases 8 months later and began gefitinib treatment. The lung lesions re-grew 15 months later, and EGFR T790M mutation was detected in the lung metastasis re-biopsy. She was administered osimertinib; however, it relapsed with pleural effusion 16 months later. We isolated cells from the osimertinib-resistant pleural effusion to establish a novel cell line, ABC-31.

Results

Although the EGFR L858R mutation was detected in ABC-31 cells, the T790M mutation was lost. ABC-31 cells were resistant to EGFR-TKIs, including osimertinib. Phospho-receptor tyrosine kinase array revealed activation of the insulin-like growth factor 1 receptor (IGF1R), whereas overexpression of the IGF1R ligand, IGF2, induced IGF1R activation in ABC-31 cells. Combination therapy using EGFR-TKIs and IGF1R inhibitor acted synergistically in vitro. She was re-administered osimertinib since EGFR-TKIs and IGF1R inhibitor combination therapy was impossible in clinical practice. This had a slight and short-lived effect.

Conclusions

Taken together, we have successfully established a new osimertinib-resistant lung adenocarcinoma cell line with activated IGF1R. These ABC-31 cells will help develop novel therapeutic strategies for patients with lung adenocarcinoma resistant to specific treatment via IGF1R activation.
BRAFV600E Mutation in First-Line Metastatic Colorectal Cancer: An Analysis of Individual Patient Data From the ARCAD Database
Authors: Cohen Romain , Liu Heshan , Fiskum Jack , Adams Richard , Chibaudel Benoist , Maughan Timothy S , Van Cutsem Eric , Venook Alan , Douillard Jean-Yves , Heinemann Volker , Ja Punt Cornelis , Falcone Alfredo , Bokemeyer Carsten , Kaplan Richard , Lenz Heinz-Josef , Koopman Miriam , Yoshino Takayuki , Zalcberg John , Grothey Alex , de Gramont Aimery , Shi Qian , André Thierry
Published: March 2021

Background

First-line therapeutic strategies for patients with BRAFV600E-mutated (BRAFmt) metastatic colorectal cancer (mCRC) mainly rely on subgroup analyses from randomized controlled trials (RCTs). We aimed to assess the prognostic and predictive impact of BRAFmt on the efficacy of targeted therapies with first-line chemotherapy.

Methods

Individual patient data from first-line RCTs with BRAF and KRAS status data in the ARCAD database were pooled. Progression-free survival and overall survival (OS) were assessed using Kaplan-Meier and Cox models. Outcomes were compared between treatment groups that were concurrently randomly assigned whenever possible.

Results

A total of 6391 patients from 10 RCTs were included: 573 BRAFmt (9.0%), 2059 KRASmt (32.2%), and 3759 double wild type (58.8%). BRAFmt mCRC patients experienced statistically significantly poorer OS than those with KRASmt (adjusted hazard ratio [HRadj] = 1.46, 95% confidence interval [CI] = 1.30 to 1.64) and patients with double wild-type tumors (HRadj = 2.14, 95% CI = 1.94 to 2.36). Anti-EGFR agents did not improve progression-free survival or OS of BRAFmt mCRC patients, based on 4 RCTs testing chemotherapy with or without anti-epidermal growth factor receptor (anti-EGFR) (HRadj = 0.96, 95% CI = 0.71 to 1.30; and HRadj = 0.85, 95% CI = 0.66 to 1.14, respectively).

Conclusions

Our data suggest that the addition of anti-EGFR agents to chemotherapy is ineffective as first-line treatment for BRAFmt mCRC patients.
All Hands on Deck: Addressing Adolescent Depression in Pediatric Primary Care
Authors: Kenny Jessica , Costello Lisa , Kelsay Kim , Bunik Maya , Xiong Shengh , Chiaravalloti Lauren , Millar Amanda , Talmi Ayelet
Published: March 2021

Objective

This study examines prevalence rates of elevated depression symptoms utilizing the Patient Health Questionnaire-9 Item Modified for Adolescents (PHQ-9A), characterizes recommendations and interventions by primary care providers (PCPs) and behavioral health clinicians (BHCs) in response to elevated PHQ-9As, and identifies factors associated with improved PHQ-9A scores at follow-up pediatric primary care visits.

Methods

A mixed methods approach was taken. Visit data, demographics, and PHQ-9A scores for 2,107 adolescents aged 11–18 were extracted using clinical informatics between January 3, 2017 and August 31, 2018. Descriptive statistics and chi-square analyses were conducted, followed by conventional content analysis of electronic medical records to examine qualitative results. Qualitative analyses were transformed into quantitative results and analyzed using point biserial correlations.

Results

Of the 2,107 adolescents, 277 (13%) had an elevated PHQ-9A. Content analysis resulted in 40 actions (17 PCP codes, 23 BHC codes) in response to an elevated PHQ-9A. Significant correlations were found between an improved PHQ-9A at a follow-up visit and the PCP referring to integrated behavioral health (r = .20, p < .01), and BHCs recommending and checking in at a follow-up visit (r = .20, p < .05), conducting a risk assessment (r = .15, p < .05), and providing psychoeducation about mood symptoms (r = .15, p < .05).

Conclusions

Primary care is an ideal setting to address the public health crisis of untreated adolescent depression. Implications for screening processes, practice implications for PCPs and BHCs, future directions, and limitations are discussed.
Scale-dependent anisotropy of electric field fluctuations in solar wind turbulence
Authors: Deepali Deepali , Banerjee Supratik
Published: March 2021

We study the variation of average powers and spectral indices of electric field fluctuations with respect to the angle between average flow direction and the mean magnetic field in solar wind turbulence. Cluster spacecraft data from the years 2002 and 2007 are used for the present analysis. We perform a scale-dependent study with respect to the local mean magnetic field using wavelet analysis technique. Prominent anisotropies are found for both the spectral index and power levels of the electric power spectra. Similar to the magnetic field fluctuations, the parallel (or antiparallel) electric fluctuation spectrum is found to be steeper than the perpendicular spectrum. However, the parallel (or antiparallel) electric power is found to be greater than the perpendicular one. Below 0.1 Hz, the slope of the parallel electric power spectra deviates substantially from that of the total magnetic power spectra, supporting the existence of Alfvénic turbulence.
Can’t Work From Home: Pooled Nucleic Acid Testing of Laboratory Workers During the COVID-19 Pandemic
Authors: Rawlings Stephen A , Scott Brianna , Layman Laura , Naranatt Pramod , Heltsley Roy , Ignacio Caroline , Porrachia Magali , Gianella Sara , Smith Davey , Chaillon Antoine
Published: March 2021

Together with protective measures, routine screening for severe acute respiratory syndrome coronavirus 2 infection helps provide a safe working environment. We evaluated a pooled nucleic acid testing strategy in a research laboratory. It allowed lab activity to be maintained and would save 25 920 person-hours and $1 684 800/year by increasing the margin of safety for returning to work.
Transpalpebral Superolateral Orbitotomy for Orbital Cavernous Hemangioma Extirpation: 2-Dimensional Operative Video
Authors: May Adrien T , Guatta Ramona , Meling Torstein R
Published: March 2021

Cavernous hemangiomas of the orbit are low-pressure vascular tumors. Usually benign, they become symptomatic by the local mass effect, pushing the eyeball forward, causing exophthalmia, by oculomotor muscle and nerve compression causing diplopia or by optic nerve compression, leading to visual impairment.

 Radiotherapy is of limited value in their treatment because of the fragility of the optic nerve and subsequent blindness risk. Surgery remains the gold standard and definitive treatment. We illustrate in this video a transpalpebral superolateral orbitotomy and extirpation of an orbital cavernous hemangioma.

 A 52-yr-old healthy woman was sent for neurosurgical consultation by her ophthalmologist. She described a history of progressive unilateral right exophthalmia in the last months. A cerebral magnetic resonance imaging (MRI) revealed a 2.5-cm-large orbital lesion located superiorly and laterally to the eyeball. Surgery was proposed and accepted by the patient. The frontozygomatic component of the orbital rim needed to be removed to safely extirpate the cavernous hemangioma without exerting unnecessary and risky pressure on the eyeball.
1,2
We decided to go for a superolateral orbitotomy via a transpalpebral incision.
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Total removal of the lesion was achieved with no complication. Exophthalmia normalized.

 Written patient consent was obtained for use and publication of their image after complete information. The patient consented to the surgery.