bluuebunny/crossref_metadata_2025 huggingface dataset:
Early risk assessment in paediatric and adult household contacts of confirmed tuberculosis cases by novel diagnostic tests (ERASE-TB): protocol for a prospective, non-interventional, longitudinal, multicountry cohort study
Authors: Marambire Edson Tawanda , Banze Denise , Mfinanga Alfred , Mutsvangwa Junior , Mbunda Theodora D , Ntinginya Nyanda Elias , Celso Khosa , Kallenius Gunilla , Calderwood Claire J , Geldmacher Christof , Held Kathrin , Appalarowthu Tejaswi , Rieß Friedrich , Panzner Ursula , Heinrich Norbert , Kranzer Katharina
Published: July 2022

Introduction

The WHO End-TB Strategy calls for the development of novel diagnostics to detect tuberculosis (TB) earlier and more accurately. Better diagnostics, together with tools to predict disease progression, are critical for achieving WHO End-TB targets. The Early Risk Assessment in TB Contacts by new diagnoStic tEsts (ERASE-TB) study aims to evaluate novel diagnostics and testing algorithms for early TB diagnosis and accurate prediction of disease progression among household contacts (HHCs) exposed to confirmed index cases in Mozambique, Tanzania and Zimbabwe.

Methods and analysis

A total of 2100 HHCs (aged ≥10 years) of adults with microbiologically-confirmed pulmonary TB will be recruited and followed up at 6-month intervals for 18–24 months. At each time point, a WHO symptom screen and digital chest radiograph (dCXR) will be performed, and blood and urine samples will be collected. Individuals screening positive (WHO symptom screen or dCXR) will be requested to provide sputum for Xpert MTB/Rif Ultra. At baseline, HHCs will also be screened for HIV, diabetes (HbA1c), chronic lung disease (spirometry), hypertension and anaemia. Study outcomes will be coprevalent TB (diagnosed at enrolment), incident TB (diagnosed during follow-up) or no TB at completion of follow-up. Novel diagnostics will be validated using fresh and biobanked samples with a nested case–control design. Cases are defined as HHCs diagnosed with TB (for early diagnosis) or with incident TB (for prediction of progression) and will be matched by age, sex and country to HHCs who remain healthy (controls). Statistical analyses will include assessment of diagnostic accuracy by constructing receiver operating curves and calculation of sensitivity and specificity.

Ethics and dissemination

ERASE-TB has been approved by regulatory and ethical committees in each African country and by each partner organisation. Consent, with additional assent for participants <18 years, is voluntary. Attestation by impartial witnesses is sought in case of illiteracy. Confidentiality of participants is being maintained throughout. Study findings will be presented at scientific conferences and published in peer-reviewed international journals.

Trial registration number

NCT04781257.Cite Now
Short- and long-term survival after ST-elevation myocardial infarction treated with pharmacoinvasive versus primary percutaneous coronary intervention strategy: a prospective cohort study
Authors: Kvakkestad Kristin , Gran Jon Michael , Halvorsen Sigrun
Published: July 2022

Objective

Compare survival in patients with ST-elevation myocardial infarction (STEMI) treated with a pharmacoinvasive (PI) or primary percutaneous coronary intervention (pPCI) strategy based on estimated time to PCI.

Design

Prospective observational cohort study. Consecutive STEMI patients were registered on admission to our PCI centre and classified in a PI or pPCI group, based on the reperfusion strategy chosen in the prehospital or local hospital location. Time and cause of death was provided by the Norwegian Cause of Death registry. Mortality at 30 days, Kaplan-Meier survival and incidence of cardiovascular (CV) death was estimated. Adjusted effect of PI versus pPCI strategy on survival was estimated using logistic and Cox regression and propensity score weighting.

Setting

Single-centre registry in Norway during 2005–2011, within a regional STEMI network allocating patients to a PI strategy if estimated time to PCI >120 min.

Primary outcomes

30-day mortality and survival during follow-up.

Secondary outcome

Incidence of CV death during follow-up.

Results

4061 STEMI patients <80 years were included, 527 (13%) treated with a PI strategy and 3534 (87%) with a pPCI strategy. Median symptom-to-needle time was 110 min (25–75th percentile 75–163) in the PI group vs symptom-to-balloon 230 min (149–435) in the pPCI group. 30-day mortality was 3.2% and 5.0% in the PI and pPCI groups (ORadjusted0.58 (95% CI 0.30 to 1.13)) and 8-year survival was 85.9% (95% CI 80.9% to 89.6%) and 79.3% (95% CI 76.9% to 81.6%), respectively (HRadjusted 0.72 (95% CI 0.53 to 0.99)). Unadjusted incidence of 8-year CV death was 7.0% (95% CI 4.4% to 10.4%) in the PI group vs 12.4% (95% CI 9.9% to 15.2%) in the pPCI group. Adjusted long-term CV death was also lower in the PI group.

Conclusion

STEMI patients treated with a PI strategy experienced better survival compared with a pPCI strategy, also when adjusting for baseline characteristics. This supports using a PI strategy for eligible STEMI patients when pPCI cannot be performed within 120 min.
Health Equity and Its Economic Determinants (HEED): protocol for a pan-European microsimulation model for health impacts of income and social security policies
Authors: Katikireddi Srinivasa Vittal , Kopasker Daniel , Pearce Anna , Leyland Alastair H , Rostila Mikael , Richiardi Matteo
Published: July 2022

Introduction

Government policies on taxation and social security are important determinants of population health outcomes and health inequalities. However, there is a shortage of evidence to inform policymakers of the health consequences of such policies. The Health Equity and Its Economic Determinants project aims to assess the potential impacts of different taxation and social security policies across Europe on population health and health inequalities using a computer-based simulation that provides projections over multiple health domains.

Methods and analysis

In the first phase, key input parameters for the model will be estimated using estimation techniques that control for the effects of prior exposure on time-varying confounders and mediators (g-methods). The second phase will involve developing and validating the microsimulation model for the UK. Policy proposals, developed with policymakers, will be simulated in the third phase to investigate the impacts of income tax and social security changes on population health and health inequalities. In the final phase, the microsimulation model will be extended across other European countries.

Ethics and dissemination

This project will use deidentified secondary data for which ethical approval and consents were received by the original data collectors. No further ethical approval will be required for our main analytical datasets. Dissemination plans include academic publications, conference presentations, accessible policy briefings, mass media engagement and a project website. Both the syntax and the underlying synthetic data for the HEED microsimulation model will be made freely available through GitHub and the project website.
‘Everyone should know what they’re on’: a qualitative study of attitudes towards and use of patient held lists of medicines among patients, carers and healthcare professionals in primary and secondary care settings in Ireland
Authors: O'Donovan Bernadine , Kirke Ciara , Pate Muriel , Mc Hugh Sheena M , Bennett Kathleen E , Cahir Caitriona
Published: July 2022

Objectives

Managing multiple medicines can be challenging for patients with multimorbidity, who are at high risk of adverse outcomes, for example, hospitalisation. Patient-held medication lists (PHMLs) can contribute to patient safety and potentially reduce medication errors. The aims of this study are to investigate attitudes towards and use of PHMLs among healthcare professionals (HCPs), patients and carers.

Design

Qualitative study based on 39 semistructured telephone interviews.

Setting

Primary and secondary care settings in Ireland.

Participants

Twenty-one HCPs and 18 people taking medicines and caregivers.

Methods

Telephone interviews were conducted with HCPs, people taking multiple medicines (5+ medicines) and carers of people taking medicines who were purposively sampled via social media, patient groups and research collaborators. Interviews were transcribed and thematically analysed based on the Framework approach, with the Consolidated Framework for Implementation Research and Theoretical Domains Framework.

Results

Three core themes emerged: (1) attitudes to PHML, (2) function and preferred features of PHML and (3) barriers and facilitators to future use of PHML. All participating (patients/carers and HCP) groups considered PHML beneficial for patients and HCPs (eg, empowering for patients and improved adherence). While PHML were used in a variety of situations such as emergencies, concerns about their accuracy were shared across all groups. HCPs and patients differed on the level of detail that should be included in PHML. HCPs’ time constraints, patients’ multiple medicines and cognitive impairments were reported barriers. Key facilitators included access to digital/compact lists and promotion of lists by appropriate HCPs.

Conclusions

Our findings provide insight into the factors that influence use of PHML. Lists were used in a variety of settings, but there were concerns about their accuracy. A range of list formats and encouragement from key HCPs could increase the use of PHML.
From living systematic reviews to meta-analytical research domains
Authors: Cuijpers Pim , Miguel Clara , Papola Davide , Harrer Mathias , Karyotaki Eirini
Published: July 2022

Because of the rapidly increasing number of randomised controlled trials (RCTs) and meta-analyses in many fields, there is an urgent need to step up from meta-analyses to higher levels of aggregation of outcomes of RCTs. Network meta-analyses and umbrella reviews allow higher levels of aggregation of RCT outcomes, but cannot adequately cover the evidence for a whole field. The ‘Meta-Analytic Research Domain’ (MARD) may be a new methodology to aggregate RCT data of a whole field. A MARD is a living systematic review of a research domain that cannot be covered by one PICO. For example, a MARD of psychotherapy for depression covers all RCTs comparing the effects of all types of psychotherapy to control conditions, to each other, to pharmacotherapy and combined treatment. It also covers all RCTs comparing treatment formats, the effects in different target groups, subtypes of depression and secondary outcomes. Although the time and resources needed to build a MARD are considerable, they offer many advantages, including a comprehensive and consistent overview of a research field and important meta-analytic studies that cannot be conducted with conventional methods. MARDs are a promising method to step up the aggregation of RCTs to a next level and it is highly relevant to work out the methods of this approach in a more detailed way.
Arctic fleas are not fussy eaters: Bartonella bacteria may hitchhike between birds and mammals in a tundra ecosystem
Authors: Buhler Kayla J. , Agar Breeze , Galloway Terry , Alisauskas Ray , Jenkins Emily
Published: July 2022

Within the terrestrial Arctic ecosystem at Karrak Lake, Nunavut, Bartonella bacteria ( B. vinsonii subsp. berkhoffii and B. henselae) have been detected in avian nest fleas ( Ceratophyllus vagabundus vagabundus) and the blood of Arctic foxes ( Vulpes lagopus (Linnaeus, 1758)). We further investigate the transmission dynamics at Karrak Lake by identifying Bartonella present in rodents, migratory geese upon arrival to nesting grounds, and rodent and avian fleas. Conventional PCR targeting the 16S–23S rRNA intergenic transcribed spacer region revealed DNA of B. vinsonii subsp. berkhoffii and B. rochalimae in 42% of 24 nest flea pools, B. rochalimae and B. grahamii in 70% of 10 rodent flea pools ( Amalaraeus dissimilis), B. grahamii, B. vinsonii subsp. berkhoffii, and Bartonella sp. BvS12 in 20% of 20 red-backed voles ( Myodes rutilus (Pallas, 1779)), and B. vinsonii subsp. berkhoffii in 2% of 42 Ross's geese ( Anser rossii Cassin, 1861). These findings suggest that geese and their associated fleas serve as migratory hosts and vectors. Detection of the same or similar species of Bartonella in rodent fleas, nest fleas, and foxes proposes that transmission may occur during predation, and detection of B. rochalimae (a Bartonella species commonly detected in rodents) in nest fleas may suggest that these fleas have generalist feeding tendencies, acquiring Bartonella from rodents or foxes as they visit nests.
Anisomycin inhibits angiogenesis, growth, and survival of triple-negative breast cancer through mitochondrial dysfunction, AMPK activation, and mTOR inhibition
Authors: Yang Wenjuan , Zhou Cuiling , Sun Qiushi , Guan Gege
Published: July 2022

Aberrant upregulation of mitochondrial biogenesis is observed in breast cancer and holds potential therapeutic option. In our work, we showed that inhibition of mitochondrial function by anisomycin is effective against triple-negative breast cancer (TNBC). Anisomycin inhibits growth and induces caspase-dependent apoptosis in a panel of TNBC cell lines. Of note, anisomycin at a tolerable dose remarkably suppresses growth of TNBC in mice. In addition, anisomycin effectively targets breast cancer angiogenesis through inhibiting capillary network formation, migration, proliferation, and survival. Mechanistic studies show that although anisomycin activates p38 and JNK, their activations are not required for anisomycin's action. In contrast, anisomycin inhibits mitochondrial respiration, and decreases mitochondrial membrane potential and adenosine triphosphate (ATP) level. The inhibitory effect of anisomycin is significantly reversed in mitochondria respiration-deficient ρ0 cells. As a consequence, anisomycin activates AMPK and inhibits mammalian target-of-rapamycin signaling pathways. Our work demonstrated that anisomycin is a useful addition to the treatment armamentarium for TNBC.
Deer Velvet Antler Extracts Exert Anti-Inflammatory and Anti-Arthritic Effects on Human Rheumatoid Arthritis Fibroblast-Like Synoviocytes and Distinct Mouse Arthritis
Authors: Cheng Wei-Jen , Yang Hsuan-Tzu , Chiang Chih-Chao , Lai Kuei-Hung , Chen Yu-Li , Shih Huei-Lin , Kuo Jong-Jen , Hwang Tsong-Long , Lin Chi-Chien
Published: July 2022

Rheumatoid arthritis (RA) is a chronic autoimmune disease that causes joint deformity and disability. Deer velvet antler (DA), a traditional Chinese medicine, has been used to treat various types of arthritis for several thousands of years, but the underlying mechanisms are unknown. Herein, we investigated the anti-arthritic and anti-inflammatory effects of DA in vitro and in vivo. The ethyl acetate layer of DA ethanol extract (DA-EE-EA) was used to treat tumor necrosis factor (TNF)-[Formula: see text]-stimulated fibroblast-like synoviocyte MH7A cells, collagen-induced arthritis DBA/1 mice, and SKG mice with zymosan-induced arthritis. DA-EE-EA reduced nitric oxide production, prostaglandin E2 levels, and levels of pro-inflammatory cytokines including interleukin (IL)-1[Formula: see text], IL-6, and IL-8 in MH7A cells. DA-EE-EA also downregulated the phosphorylation of mitogen-activated protein kinase p38 and c-Jun N-terminal kinase and the translocation of nuclear factor kappa B p65. Intraperitoneal injection of DA-EE-EA for 3 weeks substantially reduced clinical arthritis scores in vivo models. Pathohistological images of the hind paws showed that DA-EE-EA reduced immune cell infiltration, synovial hyperplasia, and cartilage damage. The levels of pro-inflammatory cytokines, such as tumor necrosis factor alpha, IL-1[Formula: see text], IL-6, IL-8, IL-17A, and interferon-gamma, decreased in the hind paw homogenates of DA-EE-EA-treated mice. We also identified several potential components, such as hexadecanamide, oleamide, erucamide, and lysophosphatidylcholines, that might contribute to the anti-inflammatory effects of DA-EE-EA. In conclusion, DA-EE-EA has the potential to treat RA by regulating inflammatory responses. However, the individual components of DA-EE-EA and the underlying anti-inflammatory mechanisms need further investigation in future studies.
CRYPTOCURRENCY, PROFITABILITY, AND TWEETER: A MGARCH FRAMEWORK
Authors: CHEN JO-HUI , HUSSAIN SABBOR , CHENG YUN-CHEN
Published: July 2022

This paper used two frames based on the Multivariate General Autoregressive Conditional Heteroscedasticity (MGARCH) model, namely the Dynamic Conditional Correlation (DCC) and the Baba, Engle, Kraft, and Kroner (BEKK) models. DCC parameters confirmed the significant results to assess the spillover effects for return volatilities of five cryptocurrencies (Bitcoin, Dogecoin, Ethereum, Monero, and Peercoin). It indicated that cryptocurrency market returns would be volatile, connected with the time-varying pattern. Most ARCH and GARCH effects were significant in estimating the three pairs of return-mining profitability, return-Tweet, and mining profitability-Tweet. For the cryptocurrency return and profitability pair, returns depended on future price returns and cross-volatility spillover and were greater than their own volatility spillover effect. Moreover, the BEKK diagonal model was found to be the best model for return-mining profitability. The research community can also gain valuable insights into cryptocurrency investment models, offering wider future areas of research.
Electrochemical Aging and Characterization of Graphite-Polymer Based Composite Bipolar Plates for Vanadium Redox Flow Batteries
Authors: Gupta Gaurav , Satola Barbara , Komsiyska Lidiya , Harms Corinna , Hickmann Thorsten , Dyck Alexander
Published: July 2022

Three bipolar plates (BPP) comprised of a composite of polypropylene or polyvinylidene fluoride polymer and varying average graphite particle size were studied for application in a vanadium redox flow battery (VRFB). The BPPs were electrochemically aged via 3000 cyclic voltammetry curves in 1.8 M VOSO4 + 2.0 M H2SO4 electrolyte. After every 500th cycle the aging progression was determined by performing cyclic voltammetry on the bipolar plates in 0.1 M H2SO4 solution where the double layer capacitance, the quinone/hydroquinone and the vanadium species redox activity were quantitatively evaluated. Prior to the aging, the composite plates were extensively characterized using various physical methods. The performed studies reveal that the wettability, surface roughness and accessible porosity of the bipolar plates significantly influence their electrochemical stability. Cycling tests in vanadium redox flow single cells at a constant current density of 60 mA cm−2 revealed a close correlation of the cell efficiencies to the electrochemical stability of the bipolar plates. Thus, the proposed electrochemical characterization method can be an effective foresight to predict the applicability of a bipolar plate in a vanadium redox flow battery.
Mid-Infrared Photoconductive Detectors Fabricated From Solution-Processed PbSe Nanocrystals
Authors: Park Junsung , Mahfuz Mohammad M. Al , Huebner  , Ko Dong-Kyun
Published: July 2022

Polycrystalline lead selenide (PbSe) is the primary material choice for low-cost, uncooled detectors operating in the mid-wavelength infrared. The fabrication of photoconductive PbSe films is typically done through chemical bath or vapor phase deposition methods and it can benefit by adopting emerging solution-process fabrication techniques. In this study, we report the preparation of a photosensitive PbSe film derived from colloidal nanocrystal ink and demonstrate its feasibility as a photoconductive photodetector. After sensitization, the device exhibits a favorable responsivity of 1.1 A/W at 4 μm peak. The work presented here may open up new opportunities for additive manufacturing of uncooled mid-infrared sensors and imagers.
SLAMF1 is expressed and secreted by hepatocytes and the liver in nonalcoholic fatty liver disease
Authors: Gomez-Torres Oscar , Amatya Shripa , Kamberov Lilly , Dhaibar Hemangini A. , Khanna Pranshu , Rom Oren , Yurdagul Arif , Orr A. Wayne , Nunez Kelly , Thevenot Paul , Cohen Ari , Samant Hrishikesh , Alexander Jonathan S. , Burgos-Ramos Emma , Chapa-Rodriguez Adrian , Cruz-Topete Diana
Published: July 2022

This study identified for the first time SLAMF1 as a mediator of hepatocyte death in nonalcoholic fatty liver disease (NASH) and as a marker of NASH in humans. There are no pharmacological treatments available for NASH, and diagnostic tools are limited to invasive liver biopsies. Therefore, since SLAMF1 levels correlate with disease progression and SLAMF1 mediates cytotoxic effects, this protein can be used as a therapeutic target and a clinical biomarker of NASH.
Improved Multiclassification of Schizophrenia Based on Xgboost and Information Fusion for Small Datasets
Authors: Zhu Wenjing , Shen Shoufeng , Zhang Zhijun
Published: July 2022

To improve the performance in multiclass classification for small datasets, a new approach for schizophrenic classification is proposed in the present study. Firstly, the Xgboost classifier is introduced to discriminate the two subtypes of schizophrenia from health controls by analyzing the functional magnetic resonance imaging (fMRI) data, while the gray matter volume (GMV) and amplitude of low-frequency fluctuations (ALFF) are extracted as the features of classifiers. Then, the D-S combination rule of evidence is used to achieve fusion to determine the basic probability assignment based on the output of different classifiers. Finally, the algorithm is applied to classify 38 healthy controls, 16 deficit schizophrenic patients, and 31 nondeficit schizophrenic patients. 10-folds cross-validation method is used to assess classification performance. The results show the proposed algorithm with a sensitivity of 73.89%, which is higher than other classification algorithms, such as supported vector machine (SVM), logistic regression (LR),

K

-nearest neighbor (KNN) algorithm, random forest (RF), BP neural network (NN), classification and regression tree (CART), naive Bayes classifier (NB), extreme gradient boosting (Xgboost), and deep neural network (DNN). The accuracy of the fusion algorithm is higher than that of classifier based on the GMV or ALFF in the small datasets. The accuracy rate of the improved multiclassification method based on Xgboost and fusion algorithm is higher than that of other machine learning methods, which can further assist the diagnosis of clinical schizophrenia.
Estimations of the Slater Gap via Convexity and Its Applications in Information Theory
Authors: Adil Khan Muhammad , Ullah Hidayat , Saeed Tareq , Alsulami Hamed H. , Sayed Z. M. M. M. , Alshehri Ahmed Mohammed
Published: July 2022

Convexity has played a prodigious role in various areas of science through its properties and behavior. Convexity has booked record developments in the field of mathematical inequalities in the recent few years. The Slater inequality is one of the inequalities which has been acquired with the help of convexity. In this note, we obtain some estimations for the Slater gap while dealing with the notion of convexity in an extensive manner. We acquire the deliberated estimations by utilizing the definition of convex function, Jensen’s inequality for concave functions, and triangular, power mean, and Hölder inequalities. We discuss several consequences of the main results in terms of inequalities for the power means. Moreover, by utilizing the main results, we give estimations for the Csiszár and Kullback–Leibler divergences, Shannon entropy, and the Bhattacharyya coefficient. Furthermore, we present some estimations for the Zipf–Mandelbrot entropy as additional applications of the acquired results. The perception and approaches adopted in this note may pretend more research in this direction.
The Investigation of HBV Pre-S/S Gene Mutations in Occult HBV Infected Blood Donors with anti-HBs Positive
Authors: Guo Yan , Lan Yu , Jing Yuanyuan , Cai Bin , Gong Hanshi , Zhang Yixin , Duan Yong
Published: July 2022

Introduction. The coexistence of hepatitis B virus (HBV) and hepatitis B surface antibodies (anti-HBs) in occult hepatitis B virus infection (OBI) is a contradictory phenomenon, and the underlying mechanism is not fully understood. The characteristics of pre-S/S mutations in OBI genotypes B and C (OBIB and OBIC) in the presence or absence of anti-HBs were analyzed extensively in this study. Methodology. The amino acid substitutions of envelope proteins of 21 OBI strains, including 4 HBs (+) OBIB, 6 HBs (−) OBIB, 6 HBs (+) OBIc, and 5 HBs (−) OBIC samples, were analyzed and fully compared among groups of HBV genotypes and the presence of anti-HBs. Results. The mutation rates in pre-S1, pre-S2, and S proteins of OBIC were significantly higher than wild-type HBV (wt-HBV) genotype C strains, but only the mutation rate of S protein in OBIB was significantly higher compared to wild-type HBV genotype B. The mutation rates in S protein of anti-HBs (−) OBI were higher than anti-HBs(+) OBI samples (4.40% vs. 2.43% in genotype B,

P
>
0.05

; 6.81% vs. 3.47% in genotype C,

P
<
0.05

). For these high-frequency substitutions in the pre-S/S region, the mutations sN40S and sK122R were found in 27.3% and 45.5% of anti-HBs (−) OBI strains, respectively. 7 substitutions were uniquely found in OBIC strains and 9 substitutions were commonly detected in OBIB and OBIC strains. Conclusions. These results suggested that the mutations might occur randomly and were not selected by antibody pressure.
Reliability and Security Analysis of Artificial Intelligence-Based Self-Driving Technologies in Saudi Arabia: A Case Study of Openpilot
Authors: Alsubaei Faisal S.
Published: July 2022

Saudi Arabia has an ambitious vision that embraces artificial intelligence (AI) technologies at a mass scale in new cities such as Neom. Self-driving has recently become one of the most important AI applications due to the advancement of sensors and AI algorithms. Given that safety is vital to the success of self-driving cars, existing infrastructures (e.g., roads and traffic signs) should be compatible with self-driving technologies. However, self-driving technologies have not been thoroughly examined in Saudi Arabia with regard to the country’s infrastructure and traffic. Therefore, this paper highlights the main areas of improvement in available self-driving technologies in Saudi Arabia. This analysis can help governments understand the current limitations of such technologies so that they can regulate them and enhance infrastructures to prepare for the mass adoption of self-driving cars. It can also help car manufacturers and developers improve self-driving algorithms to overcome their existing limitations, which will ultimately improve the safety and experience of driving.
Construction and Optimization of Artificial Intelligence-Assisted Interactive College Music Performance Teaching System
Authors: Zheng Hanwen , Dai Dandan
Published: July 2022

This research focuses on the relationship between artificial intelligence technology and music performance in colleges and universities and explores the application of artificial intelligence technology in music teaching. At the same time, it explores the deficiencies of existing computer-assisted language learning software and systems through questionnaires and interviews and also proposes solutions, such as further understanding of theories, enhancing learners’ confidence, and stimulating their interest in learning. The results of this research will help to improve the application of online intelligent human-computer systems in music teaching and provide dynamic support for improving the quality of music teaching and talent training in colleges and universities.
The Spread of Antibiotic Resistance Genes In Vivo Model
Authors: Tao Shuan , Chen Huimin , Li Na , Wang Tong , Liang Wei
Published: July 2022

Infections caused by antibiotic-resistant bacteria are a major public health threat. The emergence and spread of antibiotic resistance genes (ARGs) in the environment or clinical setting pose a serious threat to human and animal health worldwide. Horizontal gene transfer (HGT) of ARGs is one of the main reasons for the dissemination of antibiotic resistance in vitro and in vivo environments. There is a consensus on the role of mobile genetic elements (MGEs) in the spread of bacterial resistance. Most drug resistance genes are located on plasmids, and the spread of drug resistance genes among microorganisms through plasmid-mediated conjugation transfer is the most common and effective way for the spread of multidrug resistance. Experimental studies of the processes driving the spread of antibiotic resistance have focused on simple in vitro model systems, but the current in vitro protocols might not correctly reflect the HGT of antibiotic resistance genes in realistic conditions. This calls for better models of how resistance genes transfer and disseminate in vivo. The in vivo model can better mimic the situation that occurs in patients, helping study the situation in more detail. This is crucial to develop innovative strategies to curtail the spread of antibiotic resistance genes in the future. This review aims to give an overview of the mechanisms of the spread of antibiotic resistance genes and then demonstrate the spread of antibiotic resistance genes in the in vivo model. Finally, we discuss the challenges in controlling the spread of antibiotic resistance genes and their potential solutions.
Deep Learning Model of Image Classification Using Machine Learning
Authors: Lv Qing , Zhang Suzhen , Wang Yuechun
Published: July 2022

Not only were traditional artificial neural networks and machine learning difficult to meet the processing needs of massive images in feature extraction and model training but also they had low efficiency and low classification accuracy when they were applied to image classification. Therefore, this paper proposed a deep learning model of image classification, which aimed to provide foundation and support for image classification and recognition of large datasets. Firstly, based on the analysis of the basic theory of neural network, this paper expounded the different types of convolution neural network and the basic process of its application in image classification. Secondly, based on the existing convolution neural network model, the noise reduction and parameter adjustment were carried out in the feature extraction process, and an image classification depth learning model was proposed based on the improved convolution neural network structure. Finally, the structure of the deep learning model was optimized to improve the classification efficiency and accuracy of the model. In order to verify the effectiveness of the deep learning model proposed in this paper in image classification, the relationship between the accuracy of several common network models in image classification and the number of iterations was compared through experiments. The results showed that the model proposed in this paper was better than other models in classification accuracy. At the same time, the classification accuracy of the deep learning model before and after optimization was compared and analyzed by using the training set and test set. The results showed that the accuracy of image classification had been greatly improved after the model proposed in this paper had been optimized to a certain extent.
Study on the Prognosis Effect of Traditional Chinese Medicine Treatment in DR Patients Based on the Perspective of Network Pharmacology
Authors: Man Xiaoyuan , Sai Zijin
Published: July 2022

Diabetes damages the eye in many ways, but the most common eye complication is retinopathy. Of the 246 million people with diabetes worldwide, about 30% will be at risk of developing diabetic retinopathy. In addition to impairing vision, the presence of diabetic retinopathy also means an increased risk of life‐threatening systemic vascular complications. To prevent the occurrence and development of diabetic retinopathy, the research and development of new drugs for diabetic retinopathy is the primary task. Because of its characteristics of holistic view and dialectical view, traditional Chinese medicine has a good effect in the treatment of complex diseases. However, due to the characteristics of complex components, numerous targets, and synergistic effects that are important, and its compound prescriptions, the modernization of traditional Chinese medicine has been hindered. The rise of network pharmacology in recent years provides a good opportunity for the development of traditional Chinese medicine. Network pharmacology aims to explore the relationship between drugs and diseases from a holistic perspective, discover drug targets, and guide the development of new drugs. In terms of methodology, network pharmacology has the characteristics of integrity and systematicness, which just coincides with the principle of consultation in traditional Chinese medicine. In this paper, from the perspective of the application of traditional Chinese medicine, TCMSP software was used to retrieve the active ingredients in traditional Chinese medicine, and the corresponding targets of the active ingredients were obtained. We then performed GO annotation analysis and KEGG pathway analysis on the targets using DAVID software. We further used Cytoscape software to build an active ingredient‐target‐pathway network model. Through network pharmacology research, it has been shown that Fufang Xueshuantong may treat diabetic retinopathy through multiple pathways such as intravascular growth factor signaling pathway, mitogen‐activated protein kinase signaling pathway, and Toll sample receptor signaling pathway, reflecting the multicomponent traditional Chinese medicine compound and multitarget and multichannel characteristics. The research in this paper provides a theoretical basis for the pharmacological mechanism of traditional Chinese medicine in the treatment of diabetic retinopathy.
PerAnSel:  A  Novel Deep Neural Network-Based System for Persian Question Answering
Authors: Mozafari Jamshid , Kazemi Arefeh , Moradi Parham , Nematbakhsh Mohammad Ali
Published: July 2022

Question answering (QA) systems have attracted considerable attention in recent years. They receive the user’s questions in natural language and respond to them with precise answers. Most of the works on QA were initially proposed for the English language, but some research studies have recently been performed on non-English languages. Answer selection (AS) is a critical component in QA systems. To the best of our knowledge, there is no research on AS for the Persian language. Persian is a (1) free word order, (2) right-to-left, (3) morphologically rich, and (4) low-resource language. Deep learning (DL) techniques have shown promising accuracy in AS. Although DL performs very well on QA, it requires a considerable amount of annotated data for training. Many annotated datasets have been built for the AS task; most of them are exclusively in English. In order to address the need for a high-quality AS dataset in the Persian language, we present PASD; the first large-scale native AS dataset for the Persian language. To show the quality of PASD, we employed it to train state-of-the-art QA systems. We also present PerAnSel: a novel deep neural network-based system for Persian question answering. Since the Persian language is a free word-order language, in PerAnSel, we parallelize a sequential method and a transformer-based method to handle various orders in the Persian language. We then evaluate PerAnSel on three datasets: PASD, PerCQA, and WikiFA. The experimental results indicate strong performance on the Persian datasets beating state-of-the-art answer selection methods by

10.66
%

on PASD,

8.42
%

on PerCQA, and

3.08
%

on WikiFA datasets in terms of MRR.
Vulnerability of Sustainable Islamic Stock Returns to Implied Market Volatilities: An Asymmetric Approach
Authors: Alsubaie Shafi Madhkar , Mahmoud Khaled H. , Bossman Ahmed , Asafo-Adjei Emmanuel
Published: July 2022

There has been increasing interests in the sustainable way of investing as enjoined by several sustainability initiatives. However, investors require effective portfolio diversification at various market conditions (stress, benign, and boom) and would consider sustainable equities to the extent that they aid in the minimisation of portfolio risks. As a result, a better way investors can mitigate portfolio risk is by forming portfolios with relevant volatility indices as enshrined in extant literature. It becomes necessary to investigate the susceptibility of Islamic stocks in a sustainable way to shocks from volatility indices to enhance effective portfolio decisions. In this regard, we investigate the asymmetric effect of implied volatility indices on sustainable Islamic stocks across different market conditions. Hence, the quantile regression and quantile‐on‐quantile regression techniques are employed. The study discovered an asymmetric influence of volatility on sustainable Islamic stock returns at various quantiles. Furthermore, most volatilities’ asymmetric effects were generally inversely associated to sustainable Islamic stock returns, implying diversification benefits across market outcomes. Also, with the exception of the extreme quantiles, there is a causal effect of volatilities on Islamic stock returns for most quantiles. It seems to reason that ordinary market outcomes, rather than market stress or boom, have a greater impact on causal estimates for our quantile regression model.
Synthesis of a Novel Nanoparticle BaCoO2.6 through Sol‐Gel Method and Elucidation of Its Structure and Electrical Properties
Authors: Rafiq Fareenpoornima , Govindsamy Parthipan , Periyasamy Selvakumar
Published: July 2022

The physical properties of cobalt oxide with varied oxidation states, and coordination numbers, in the transition series, have numerous applications. The present study explores the physical properties of BaCoO2.6 nanoparticles synthesized through the sol‐gel method. The X‐ray diffraction figure exhibits a 25 nm crystallite size hexagonal phase. The observational data shows the reduction in the real part of impedance (Z’), dielectric constant (ξ’), dielectric loss (ξ”), and a raise in ac conductivity of mixed type of conduction with an elevation in frequency analyzed through impedance spectroscopy. The conductivity due to grain and grain boundaries is shown foremost in the complex impedance analysis. The plot of ∆V/∆T (Seebeck coefficient) in the low‐temperature range indicates p‐type behavior and the metal‐insulator transition in the as‐synthesized sample. The sample characteristics suggest applications in optical and switching devices. The Seebeck coefficient is the generation of potential difference when subjected to temperature difference. Thermoelectric materials are associated with the concept of high electrical conductivity like crystals and low thermal conductivity to that of glass. Nanothermoelectric materials can decrease further the thermal conductivity through phonon scattering. Electrical characterization suggests the presence of both NTCR and PTCR behavior in the sample, and hence, it explores the application in thermistor/resistance temperature detector’s (RTD) and low dielectric constant and loss to electro‐optical and higher conversion efficiency to storage devices. Additionally, impedance spectroscopy helps in the study of electrochemical systems and solid‐state devices wherein the transition of metal‐insulator is an add‐on to the research.
Treatment of Municipal Wastewater in a Fixed Aerated Bed: Use of Natural Fibrous Materials
Authors: Manikkampatti Palanisamy Murugesan , Mohamed Lebbai Minar , Ratnam M. Venkata
Published: July 2022

The municipal wastewater may be treated using a number of different types of fixed beds that have a larger surface area. Since the fibrous materials have such a large specific surface area, they are frequently considered to be the best option for greater microbiological support and treatment efficacy. In this research, natural fibre materials such as coir fibre and areca husk were investigated for their potential to function as fixed aerated beds for the treatment of municipal wastewater. During the experiment, variations in the chemical oxygen demand (COD), biological oxygen demand (BOD), total dissolved solids (TDS), and total suspended solids (TSS) of the effluent were used to determine how well the aerated fixed bed work in treating the wastewater. The most efficient operating parameters for the successful treatment of wastewater were determined to be a contact period of 72 hrs, a filter medium depth of 5 cm, and a packing density of 10 kg/m3. The reductions in BOD, COD, TDS, and TSS for coir fibre are 55%, 58.8%, 57.8%, and 51.89%, respectively, whereas the reductions for areca husk are 38.3%, 37.78%, 31.76%, and 30.56%, respectively. In the course of this experiment, the coir fibre was discovered to be marginally more effective in comparison to the areca husk.
Comparative Outcomes of Standard Perioperative Eye Drops, Intravitreal Triamcinolone Acetonide-Moxifloxacin, and Intracameral Dexamethasone-Moxifloxacin-Ketorolac in Cataract Surgery
Authors: Kuriakose Robin K. , Cho Soungmin , Nassiri Saman , Hwang Frank S.
Published: July 2022

Background. Since the advent of cataract surgery, topical eye drops have been the mainstay of postoperative prophylaxis and treatment. Due to factors such as high expenses and poor patient compliance, there has been a growing interest and acceptance of “dropless” or “less drops” alternatives. The purpose of this study is to compare the effectiveness of intravitreal triamcinolone acetonide-moxifloxacin and intracameral dexamethasone-moxifloxacin-ketorolac to a standard eye drop regimen in controlling postoperative inflammation, corneal edema, and intraocular pressure (IOP) among cataract patients. Methods. A retrospective longitudinal comparative study among 619 consecutive eyes receiving either a standard eye drop regimen, intraoperative triamcinolone acetonide-moxifloxacin, or dexamethasone-moxifloxacin-ketorolac was performed between October 2016 and December 2020. Primary endpoints at postoperative day one (POD1), week one (POW1), and month one (POM1) included corneal edema, anterior chamber inflammation (ACI), and IOP. Results. Throughout the postoperative time points, there were no significant differences in corneal edema between intravitreal triamcinolone acetonide-moxifloxacin versus the standard eye drop therapy (OR [95% CI]: 1.09 [0.82, 1.45],

P
=
0.54

) and intracameral dexamethasone-moxifloxacin-ketorolac versus the standard eye drop treatment (OR [95% CI]: 1.22 [0.89, 1.67],

P
=
0.22

). The postoperative ACI severity was lower in the dexamethasone-moxifloxacin-ketorolac group than in the triamcinolone acetonide-moxifloxacin group by 35% on postoperative day 1 (

P
=
0.01

). The differences at subsequent postoperative time points were not statistically significant (

P
=
0.27

and

P
=
1.00

for POW1 and POM1, respectively). IOP at POM1 follow-up visit was statistically significantly higher for the triamcinolone acetonide-moxifloxacin group (mean (±SD): 15.64 (4.26)) than the dexamethasone-moxifloxacin-ketorolac (mean (±SD): 14.16 (4.02)) (

P
<
0.01

). There was no statistical difference in rates of CME (

P
=
0.16

), and there were no cases of endophthalmitis. Conclusions. Intravitreal triamcinolone acetonide-moxifloxacin and intracameral dexamethasone-moxifloxacin-ketorolac demonstrate similar levels of efficacy to a standard eye drop regimen after cataract surgery. This study reinforces them as viable alternatives to traditional postoperative drops.
A Machine Vision Approach for Classification of Skin Cancer Using Hybrid Texture Features
Authors: Zareen Syeda Shamaila , Guangmin Sun , Li Yu , Kundi Mahwish , Qadri Salman , Qadri Syed Furqan , Ahmad Mubashir , Khan Ali Haider
Published: July 2022

The main purpose of this study is to observe the importance of machine vision (MV) approach for the identification of five types of skin cancers, namely, actinic-keratosis, benign, solar-lentigo, malignant, and nevus. The 1000 (200 × 5) benchmark image datasets of skin cancers are collected from the International Skin Imaging Collaboration (ISIC). The acquired ISIC image datasets were transformed into texture feature dataset that was a combination of first-order histogram and gray level co-occurrence matrix (GLCM) features. For the skin cancer image, a total of 137,400 (229 × 3 x 200) texture features were acquired on three nonover-lapping regions of interest (ROIs). Principal component analysis (PCA) clustering approach was employed for reducing the dimension of feature dataset. Each image acquired twenty most discriminate features based on two different approaches of statistical features such as average correlation coefficient plus probability of error (ACC + POE) and Fisher (Fis). Furthermore, a correlation-based feature selection (CFS) approach was employed for feature reduction, and optimized 12 features were acquired. Furthermore, a classification algorithm naive bayes (NB), Bayes Net (BN), LMT Tree, and multilayer perception (MLP) using 10 K-fold cross-validation approach were employed on optimized feature datasets and the overall accuracy achieved by MLP is 97.1333%.
A Unique Trinucleotide-Bloc Mutation-Based Two SARS-CoV-2 Genotypes with Potential Pathogenic Impacts
Authors: Ayub Mustak Ibn
Published: July 2022

SARS-CoV-2, the novel coronavirus behind the COVID-19 pandemic, is acquiring new mutations in its genome. Although some mutations provide benefits to the virus against human immune response, others may result in their reduced pathogenicity and virulence. By analyzing more than 3000 high-coverage, complete sequences deposited in the GISAID database up to April 2020, here I report the uniqueness of the 28881–28883: GGG > AAC trinucleotide-bloc mutation in the SARS-CoV-2 genome that results in two substrains, described here as SARS-CoV-2g (28881–28883: GGG genotype) and SARS-CoV-2a (28881–28883: AAC genotype). Computational analysis and literature review suggest that this bloc mutation would bring 203–204: RG (arginine-glycine)>KR (lysine-arginine) amino acid changes in the nucleocapsid (N) protein affecting the SR (serine-arginine)-rich motif of the protein, a critical region for the transcription of viral RNA and replication of the virus. Thus, 28881–28883: GGG > AAC bloc mutation is expected to modulate the pathogenicity of SARS-CoV-2. These analyses suggest that SARS-CoV-2 has evolved into SARS-CoV-2a affecting COVID-19 infectivity and severity. To confirm these assumptions, retrospective and prospective epidemiological studies should be conducted in different countries to understand the course of pathogenicity of SARS-CoV-2a and SARS-CoV-2g. Laboratory research should focus on the bloc mutation to understand its true impacts on the course of the pandemic. Potential drug and vaccine development should also keep the 28881–28883 region of the N protein under consideration.