Review on the Evaluation and Development of Artificial Intelligence for COVID-19 Containment.

Artificial intelligence has significantly enhanced the research paradigm and spectrum with a substantiated promise of continuous applicability in the real world domain. Artificial intelligence, the driving force of the current technological revolution, has been used in many frontiers, including education, security, gaming, finance, robotics, autonomous systems, entertainment, and most importantly the healthcare sector. With the rise of the COVID-19 pandemic, several prediction and detection methods using artificial intelligence have been employed to understand, forecast, handle, and curtail the ensuing threats. In this study, the most recent related publications, methodologies and medical reports were investigated with the purpose of studying artificial intelligence's role in the pandemic. This study presents a comprehensive review of artificial intelligence with specific attention to machine learning, deep learning, image processing, object detection, image segmentation, and few-shot learning studies that were utilized in several tasks related to COVID-19. In particular, genetic analysis, medical image analysis, clinical data analysis, sound analysis, biomedical data classification, socio-demographic data analysis, anomaly detection, health monitoring, personal protective equipment (PPE) observation, social control, and COVID-19 patients' mortality risk approaches were used in this study to forecast the threatening factors of COVID-19. This study demonstrates that artificial-intelligence-based algorithms integrated into Internet of Things wearable devices were quite effective and efficient in COVID-19 detection and forecasting insights which were actionable through wide usage. The results produced by the study prove that artificial intelligence is a promising arena of research that can be applied for disease prognosis, disease forecasting, drug discovery, and to the development of the healthcare sector on a global scale. We prove that artificial intelligence indeed played a significantly important role in helping to fight against COVID-19, and the insightful knowledge provided here could be extremely beneficial for practitioners and research experts in the healthcare domain to implement the artificial-intelligence-based systems in curbing the next pandemic or healthcare disaster.

Controlling Intermolecular Interaction and Interphase Chemistry Enabled Sustainable Water-tolerance LiMn2 O4 ||Li4 Ti5 O12 Batteries.

Solid electrolyte interphase (SEI) formation and H2 O activity reduction in Water-in-Salt electrolytes (WiSE) with an enlarged stability window of 3.0 V have provided the feasibility of the high-energy-density aqueous Li-ion batteries. Here, we extend the cathodic potential of WiSE by rationally controlling intermolecular interaction and interphase chemistry with the introduction of trimethyl phosphate (TMP) into WiSE. The TMP not merely limits the H2 O activity via the strong interaction between TMP and H2 O but also contributes to the formation of reinforced SEI involving phosphate and LiF by manipulating the Li+ solvation structure. Thus, water-tolerance LiMn2 O4 (LMO)||Li4 Ti5 O12 (LTO) full cell with a P/N ratio of 1.14 can be assembled and achieve a long cycling life of 1000 times with high coulombic efficiency of >99.9 %. This work provides a promising insight into the cost-effective practical manufacture of LMO||LTO cells without rigorous moisture-free requirements.

Deoxynucleoside Therapy for Thymidine Kinase 2-Deficient Myopathy.

OBJECTIVE: Thymidine kinase 2, encoded by the nuclear gene TK2, is required for mitochondrial DNA maintenance. Autosomal recessive TK2 mutations cause depletion and multiple deletions of mtDNA that manifest predominantly as a myopathy usually beginning in childhood and progressing relentlessly. We investigated the safety and efficacy of deoxynucleoside monophosphate and deoxynucleoside therapies. METHODS: We administered deoxynucleoside monophosphates and deoxynucleoside to 16 TK2-deficient patients under a compassionate use program. RESULTS: In 5 patients with early onset and severe disease, survival and motor functions were better than historically untreated patients. In 11 childhood and adult onset patients, clinical measures stabilized or improved. Three of 8 patients who were nonambulatory at baseline gained the ability to walk on therapy; 4 of 5 patients who required enteric nutrition were able to discontinue feeding tube use; and 1 of 9 patients who required mechanical ventilation became able to breathe independently. In motor functional scales, improvements were observed in the 6-minute walk test performance in 7 of 8 subjects, Egen Klassifikation in 2 of 3, and North Star Ambulatory Assessment in all 5 tested. Baseline elevated serum growth differentiation factor 15 levels decreased with treatment in all 7 patients tested. A side effect observed in 8 of the 16 patients was dose-dependent diarrhea, which did not require withdrawal of treatment. Among 12 other TK2 patients treated with deoxynucleoside, 2 adults developed elevated liver enzymes that normalized following discontinuation of therapy. INTERPRETATION: This open-label study indicates favorable side effect profiles and clinical efficacy of deoxynucleoside monophosphate and deoxynucleoside therapies for TK2 deficiency. ANN NEUROL 2019;86:293-303.

Small area estimation of under-5 mortality in Bangladesh, Cameroon, Chad, Mozambique, Uganda, and Zambia using spatially misaligned data.

BACKGROUND: The under-5 mortality rate (U5MR) is an important metric of child health and survival. Country-level estimates of U5MR are readily available, but efforts to estimate U5MR subnationally have been limited, in part, due to spatial misalignment of available data sources (e.g., use of different administrative levels, or as a result of historical boundary changes). METHODS: We analyzed all available complete and summary birth history data in surveys and censuses in six countries (Bangladesh, Cameroon, Chad, Mozambique, Uganda, and Zambia) at the finest geographic level available in each data source. We then developed small area estimation models capable of incorporating spatially misaligned data. These small area estimation models were applied to the birth history data in order to estimate trends in U5MR from 1980 to 2015 at the second administrative level in Cameroon, Chad, Mozambique, Uganda, and Zambia and at the third administrative level in Bangladesh. RESULTS: We found substantial variation in U5MR in all six countries: there was more than a two-fold difference in U5MR between the area with the highest rate and the area with the lowest rate in every country. All areas in all countries experienced declines in U5MR between 1980 and 2015, but the degree varied both within and between countries. In Cameroon, Chad, Mozambique, and Zambia we found areas with U5MRs in 2015 that were higher than in other parts of the same country in 1980. Comparing subnational U5MR to country-level targets for the Millennium Development Goals (MDG), we find that 12.8% of areas in Bangladesh did not meet the country-level target, although the country as whole did. A minority of areas in Chad, Mozambique, Uganda, and Zambia met the country-level MDG targets while these countries as a whole did not. CONCLUSIONS: Subnational estimates of U5MR reveal significant within-country variation. These estimates could be used for identifying high-need areas and positive deviants, tracking trends in geographic inequalities, and evaluating progress towards international development targets such as the Sustainable Development Goals.

The Role of Noncomparative Evidence in Health Technology Assessment Decisions.

BACKGROUND: Many health technology assessment (HTA) agencies express a preference for randomized controlled trial evidence when appraising health technologies; nevertheless, it is not always feasible or ethical to conduct such comparative trials. OBJECTIVES: To assess the role of noncomparative evidence in HTA decision making. METHODS: The Web sites of the National Institute for Health and Care Excellence (NICE) in the United Kingdom, the Canadian Agency for Drugs and Technologies in Health (CADTH) in Canada, and the Institute for Quality and Efficiency in Health Care (Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen [IQWiG]) in Germany were searched for single HTA reports (published between January 2010 and December 2015). The product, indication, outcome, and clinical evidence presented (comparative/noncomparative) were double-extracted, with any discrepancies reconciled. A noncomparative study was defined as any study not presenting results against another treatment (including placebo or best supportive care), regardless of phase or setting, including dose-ranging studies. RESULTS: A total of 549 appraisals were extracted. Noncomparative evidence was considered in 38% (45 of 118) of NICE submissions, 13% (34 of 262) of CADTH submissions, and 12% (20 of 169) of IQWiG submissions. Evidence submissions based exclusively on noncomparative evidence were presented in only 4% (5 of 118) of NICE appraisals, 6% (16 of 262) of CADTH appraisals, and 4% (6 of 169) of IQWiG appraisals. Most drugs appraised solely on the basis of noncomparative evidence were indicated for cancer or hepatitis C. Positive outcome rates (encompassing recommended/restricted/added-benefit decisions) for submissions presenting only noncomparative evidence were similar to overall recommendation rates for CADTH (69% vs. 68%, respectively), but were numerically lower for NICE (60% vs. 84%, respectively) and IQWiG (17% vs. 38%, respectively) (P > 0.05 for all). CONCLUSIONS: Noncomparative studies can be viewed as acceptable clinical evidence by HTA agencies when these study designs are justifiable and when treatment effect can be convincingly demonstrated, but their use is currently limited.

Impact of mobile phone-based technology to improve health, population and nutrition services in Rural Bangladesh: a study protocol.

BACKGROUND: Mobile phone-based technology has been used in improving the delivery of healthcare services in many countries. However, data on the effects of this technology on improving primary healthcare services in resource-poor settings are limited. The aim of this study is to develop and test a mobile phone-based system to improve health, population and nutrition services in rural Bangladesh and evaluate its impact on service delivery. METHODS: The study will use a quasi-experimental pre-post design, with intervention and comparison areas. Outcome indicators will include: antenatal care (ANC), delivery care, postnatal care (PNC), neonatal care, expanded programme on immunization (EPI) coverage, and contraceptive prevalence rate (CPR). The study will be conducted over a period of 30 months, using the existing health systems of Bangladesh. The intervention will be implemented through the existing service-delivery personnel at various primary-care levels, such as community clinic, union health and family welfare centre, and upazila health complex. These healthcare providers will be given mobile phones equipped with Apps for sending text and voice messages, along with the use of Internet and device for data-capturing. Training on handling of the Smartphones, data-capturing and monitoring will be given to selected service providers. They will also be trained on inputs, editing, verifying, and monitoring the outcome variables. DISCUSSION: Mobile phone-based technology has the potential to improve primary healthcare services in low-income countries, like Bangladesh. It is expected that our study will contribute to testing and developing a mobile phone-based intervention to improve the coverage and quality of services. The learning can be used in other similar settings in the low-and middle-income countries.

A Molten Salt Lithium-Oxygen Battery.

Despite the promise of extremely high theoretical capacity (2Li + O2 ↔ Li2O2, 1675 mAh per gram of oxygen), many challenges currently impede development of Li/O2 battery technology. Finding suitable electrode and electrolyte materials remains the most elusive challenge to date. A radical new approach is to replace volatile, unstable and air-intolerant organic electrolytes common to prior research in the field with alkali metal nitrate molten salt electrolytes and operate the battery above the liquidus temperature (>80 °C). Here we demonstrate an intermediate temperature Li/O2 battery using a lithium anode, a molten nitrate-based electrolyte (e.g., LiNO3-KNO3 eutectic) and a porous carbon O2 cathode with high energy efficiency (∼95%) and improved rate capability because the discharge product, lithium peroxide, is stable and moderately soluble in the molten salt electrolyte. The results, supported by essential state-of-the-art electrochemical and analytical techniques such as in situ pressure and gas analyses, scanning electron microscopy, rotating disk electrode voltammetry, demonstrate that Li2O2 electrochemically forms and decomposes upon cycling with discharge/charge overpotentials as low as 50 mV. We show that the cycle life of such batteries is limited only by carbon reactivity and by the uncontrolled precipitation of Li2O2, which eventually becomes electrically disconnected from the O2 electrode.

Massive deregulation of miRNAs from nuclear reprogramming errors during trophoblast differentiation for placentogenesis in cloned pregnancy.

BACKGROUND: Low efficiency of Somatic Cell Nuclear Transfer (NT) has been widely addressed with high incidence of placental abnormalities due to genetic and epigenetic modifications. MiRNAs are shown to be major regulators of such modifications. The present study has been carried out to identify the expression patterns of 377 miRNAs, their functional associations and mechanism of regulation in bovine placentas derived from artificial insemination (AI), in vitro production (IVP) and NT pregnancies. RESULTS: This study reveals a massive deregulation of miRNAs as chromosomal cluster or miRNA families without sex-linkage in NT and in-vitro derived IVP placentas. Cell specific localization miRNAs in blastocysts and expression profiling of embryos and placentas at different developmental stages identified that the major deregulation of miRNAs exhibited in placentas at day 50 of pregnancies is found to be less dependent on global DNA methylation, rather than on aberrant miRNA biogenesis molecules. Among them, aberrant AGO2 expression due to hypermethylation of its promoter was evident. Along with other factors, aberrant AGO2 expression was observed to be associated with multiple defects in trophoblast differentiation through deregulation of miRNAs mediated mechanisms. CONCLUSION: These aberrant miRNA activities might be associated with genetic and epigenetic modifications in abnormal placentogenesis due to maldifferentiation of early trophoblast cell lineage in NT and IVP pregnancies. This study provides the first insight into genome wide miRNA expression, their role in regulation of trophoblast differentiation as well as abnormal placental development in Somatic Cell Nuclear Transfer pregnancies to pave the way to improve the efficiency of cloning by nuclear transfer.

Predicting the electrochemical behavior of lithium nitrite in acetonitrile with quantum chemical methods.

Electrolyte stability is an essential prerequisite for the successful development of a rechargeable organic electrolyte Li-O2 battery. Lithium nitrate (LiNO3) salt was employed in our previous work because it was capable of stabilizing a solid-electrolyte interphase on the Li anode. The byproduct of this process is lithium nitrite (LiNO2), the fate of which in a Li-O2 battery is unknown. In this work, we employ density functional theory and coupled-cluster calculations combined with an implicit solvation model for neutral molecules and a mixed cluster/continuum model for single ions to understand the chemical and electrochemical behavior of LiNO2 in acetonitrile (AN). The redox potentials of oxygenated nitrogen compounds predicted in this study are in excellent agreement with the experimental results (the average accuracy is 0.10 V). Theoretical calculations suggest that the reaction between the nitrite ion and its first oxidation product, nitrogen dioxide (NO2), in AN solution proceeds via the initial formation of a trans-ONO-NO2 dimer that is subject to autoionization and the subsequent reaction of produced nitrosyl ion (NO(+)) with NO2(-). Good agreement between experimental and simulated cyclic voltammograms for electrochemical oxidation of LiNO2 in AN provides support to the proposed mechanism of coupled electrochemical and chemical reactions. The results suggest a possible mechanism of regeneration of LiNO3 in electrolyte in the presence of oxygen, which is uniquely possible under charging conditions in a Li-O2 battery.

Variability in interval production is due to timing-dependent deficits in Huntington's disease.

In Huntington's disease (HD), increased variability is seen in performance of motor tasks that require implicit control of timing. We examined whether timing variability was also evident in an explicit interval-timing task. Sixty subjects (21 controls, 19 manifest HD, and 20 pre-manifest HD) performed a single-interval production task with three target intervals (1.1 s, 2.2 s, 3.3 s). We analyzed accuracy (proportional error) and precision (standard deviation) across groups and intervals. No differences were seen in accuracy across groups or intervals. Precision was significantly lower in manifest (P = 0.0001) and pre-manifest HD (P = 0.04) compared with controls. This was particularly true for pre-manifest subjects close to diagnosis (based on probability of diagnosis in 5 years). Precision was correlated with proximity to diagnosis (r2 = 0.3, P < 0.01). To examine the source of reduced precision, we conducted linear regression of standard deviation with interval duration. Slope of the regression was significantly higher in manifest HD (P = 0.02) and in pre-manifest HD close to diagnosis (P = 0.04) compared with controls and pre-manifest participants far from diagnosis. Timing precision is impaired before clinical diagnosis in Huntington's disease. Slope analysis suggests that timing variability (decreased precision) was attributable to deficits in timing-dependent processes. Our results provide additional support for the proposal that the basal ganglia are implicated in central timekeeping functions. Because the single interval production task was sensitive to deficits in pre-manifest HD, temporal precision may be a useful outcome measure in future clinical trials.

Phase tunable nickel doped Mn3O4 nanoparticle synthesis by chemical precipitation: kinetic study on dye degradation.

Nickel (Ni) doped Mn3O4 nanoparticles (NPs) were synthesized by a quick and facile chemical precipitation technique to investigate their performance in the degradation of methylene blue (MB) in the absence of light. XRD, FESEM, TEM, AAS, XPS, and FT-IR were used for the investigation of the structural, surface morphological, and elemental composition of Ni doped Mn3O4 NPs. XRD confirms the formation of a tetragonal phase structure of pure Mn3O4 and 1% and 3% Ni doped Mn3O4 NPs. However, mixed phases were found in the case of 5 to 10% Ni doped Mn3O4 NPs. Well-defined spherical-shaped morphology was presented through FESEM. Particle sizes decreased linearly (58.50 to 23.68 nm) upon increasing the doping concentration from 0% (pure Mn3O4) to 7% respectively, and then increased (48.62 nm) in the case of 10% doping concentration. TEM further confirmed spherical shaped 32 nm nanoparticles for 7% Ni doped Mn3O4. The elemental composition and oxidation state of the prepared NPs were confirmed by using XPS spectra. Mixed valence Mn2+ and Mn4+ states were found in pure Mn3O4 and 1% and 3% Ni doped Mn3O4 NPs in the ratio of 2MnO-MnO2. In addition, three different oxidation states Mn2+, Mn3+, and Mn4+ were found in 5 to 10% Ni doped Mn3O4 NPs. Moreover, as a dopant Ni exists as Ni2+ and Ni3+ states in all Ni doped Mn3O4 NPs. The synthesized NPs were then applied as potent oxidants for the degradation of MB at pH 3. With the increase of doping concentration to 7%, the degree of degradation was increased to 79% in the first 10 min and finally, it became about 98%. The degradation of MB follows the pseudo-first-order linear kinetics with a degradation rate of 0.0342 min-1.

A rechargeable Li-O2 battery using a lithium nitrate/N,N-dimethylacetamide electrolyte.

A major challenge in the development of rechargeable Li-O(2) batteries is the identification of electrolyte materials that are stable in the operating environment of the O(2) electrode. Straight-chain alkyl amides are one of the few classes of polar, aprotic solvents that resist chemical degradation in the O(2) electrode, but these solvents do not form a stable solid-electrolyte interphase (SEI) on the Li anode. The lack of a persistent SEI leads to rapid and sustained solvent decomposition in the presence of Li metal. In this work, we demonstrate for the first time successful cycling of a Li anode in the presence of the solvent, N,N-dimethylacetamide (DMA), by employing a salt, lithium nitrate (LiNO(3)), that stabilizes the SEI. A Li-O(2) cell containing this electrolyte composition is shown to cycle for more than 2000 h (>80 cycles) at a current density of 0.1 mA/cm(2) with a consistent charging profile, good capacity retention, and O(2) detected as the primary gaseous product formed during charging. The discovery of an electrolyte system that is compatible with both electrodes in a Li-O(2) cell may eliminate the need for protecting the anode with a ceramic membrane.

Knowledge of, attitudes toward, and preventive practices relating to cholera and oral cholera vaccine among urban high-risk groups: findings of a cross-sectional study in Dhaka, Bangladesh.

BACKGROUND: In endemic countries such as Bangladesh, consequences of cholera place an enormous financial and social burden on patients and their families. Cholera vaccines not only provide health benefits to susceptible populations but also have effects on the earning capabilities and financial stability of the family. Community-based research and evaluations are necessary to understand perceptions about and practices of the community relating to cholera and oral cholera vaccines. This may help identify the ways in which such vaccines may be successfully introduced, and other preventive measures can be implemented. The present study assessed the knowledge of, attitudes toward, and preventive practices relating to cholera and oral cholera vaccine among an urban population residing in a high cholera-prone setting in Dhaka, Bangladesh. METHODS: This cross-sectional study was conducted in an area of high cholera prevalence in 15 randomly-selected clusters in Mirpur, Dhaka city. A study team collected data through a survey and in-depth interviews during December 2010-February 2011. RESULTS: Of 2,830 families included in the final analysis, 23% could recognize cholera as acute watery diarrhea and 16% had ever heard of oral cholera vaccine. About 54% of the respondents had poor knowledge about cholera-related issues while 97% had a positive attitude toward cholera and oral cholera vaccine. One-third showed poor practice relating to the prevention of cholera.The findings showed a significant (p < 0.05) association between the respondents' knowledge and sex, education, occupation, monthly overall household expenditure, attitudes and practice. In the adjusted model, male sex, having a lower monthly overall household expenditure, and having a less positive attitude toward cholera were the significant predictors to having poor knowledge. CONCLUSIONS: The findings suggest the strengthening of health education activities to improve knowledge on cholera, its prevention and treatment and information on cholera vaccination among high-risk populations. The data also underscore the potential of mass cholera vaccination to prevent and control cholera.

Introduction of new vaccines: decision-making process in Bangladesh.

The understanding of the decision-making process in the introduction of new vaccines helps establish why vaccines are adopted or not. It also contributes to building a sustainable demand for vaccines in a country. The purpose of the study was to map and analyze the formal decision-making process in relation to the introduction of new vaccines within the context of health policy and health systems and identify the ways of making decisions to introduce new vaccines in Bangladesh. During February-April 2011, a qualitative assessment was made at the national level to evaluate the decision-making process around the adoption of new vaccines in Bangladesh. The study population included: policy-level people, programme heads or associates, and key decision-makers of the Government, private sector, non-governmental organizations, and international agencies at the national level. In total, 13 key informants were purposively selected. Data were collected by interviewing key informants and reviewing documents. Data were analyzed thematically. The findings revealed that the actors from different sectors at the policy level were involved in the decision-making process in the introduction of new vaccines. They included policy-makers from the ministries of health and family welfare, finance, and local government and rural development; academicians; researchers; representatives from professional associations; development partners; and members of different committees on EPI. They contributed to the introduction of new vaccines in their own capacity. The burden of disease, research findings on vaccine-preventable diseases, political issues relating to outbreaks of certain diseases, initiatives of international and local stakeholders, pressure of development partners, the Global Alliance for Vaccines and Immunization (GAVI) support, and financial matters were the key factors in the introduction of new vaccines in Bangladesh. The slow introduction and uptake of new vaccines is a concern in the country. Rapid action on the application of GAVI support and less time taken by the Government in processing the implementation and administrative work may expedite the introduction of new vaccines in future in this country.

YoNet: A Neural Network for Yoga Pose Classification.

Yoga has become an integral part of human life to maintain a healthy body and mind in recent times. With the growing, fast-paced life and work from home, it has become difficult for people to invest time in the gymnasium for exercises. Instead, they like to do assisted exercises at home where pose recognition techniques play the most vital role. Recognition of different poses is challenging due to proper dataset and classification architecture. In this work, we have proposed a deep learning-based model to identify five different yoga poses from comparatively fewer amounts of data. We have compared our model's performance with some state-of-the-art image classification models-ResNet, InceptionNet, InceptionResNet, Xception and found our architecture superior. Our proposed architecture extracts spatial, and depth features from the image individually and considers them for further calculation in classification. The experimental results show that it achieved 94.91% accuracy with 95.61% precision.

Evaluating the Brexit and COVID-19's influence on the UK economy: A data analysis.

The economic landscape of the United Kingdom has been significantly shaped by the intertwined issues of Brexit, COVID-19, and their interconnected impacts. Despite the country's robust and diverse economy, the disruptions caused by Brexit and the COVID-19 pandemic have created uncertainty and upheaval for both businesses and individuals. Recognizing the magnitude of these challenges, academic literature has directed its attention toward conducting immediate research in this crucial area. This study sets out to investigate key economic factors that have influenced various sectors of the UK economy and have broader economic implications within the context of Brexit and COVID-19. The factors under scrutiny include the unemployment rate, GDP index, earnings, and trade. To accomplish this, a range of data analysis tools and techniques were employed, including the Box-Jenkins method, neural network modeling, Google Trend analysis, and Twitter-sentiment analysis. The analysis encompassed different periods: pre-Brexit (2011-2016), Brexit (2016-2020), the COVID-19 period, and post-Brexit (2020-2021). The findings of the analysis offer intriguing insights spanning the past decade. For instance, the unemployment rate displayed a downward trend until 2020 but experienced a spike in 2021, persisting for a six-month period. Meanwhile, total earnings per week exhibited a gradual increase over time, and the GDP index demonstrated an upward trajectory until 2020 but declined during the COVID-19 period. Notably, trade experienced the most significant decline following both Brexit and the COVID-19 pandemic. Furthermore, the impact of these events exhibited variations across the UK's four regions and twelve industries. Wales and Northern Ireland emerged as the regions most affected by Brexit and COVID-19, with industries such as accommodation, construction, and wholesale trade particularly impacted in terms of earnings and employment levels. Conversely, industries such as finance, science, and health demonstrated an increased contribution to the UK's total GDP in the post-Brexit period, indicating some positive outcomes. It is worth highlighting that the impact of these economic factors was more pronounced on men than on women. Among all the variables analyzed, trade suffered the most severe consequences in the UK. By early 2021, the macroeconomic situation in the country was characterized by a simple dynamic: economic demand rebounded at a faster pace than supply, leading to shortages, bottlenecks, and inflation. The findings of this research carry significant value for the UK government and businesses, empowering them to adapt and innovate based on forecasts to navigate the challenges posed by Brexit and COVID-19. By doing so, they can promote long-term economic growth and effectively address the disruptions caused by these interrelated issues.

Bio-activity prediction of drug candidate compounds targeting SARS-Cov-2 using machine learning approaches.

The SARS-CoV-2 3CLpro protein is one of the key therapeutic targets of interest for COVID-19 due to its critical role in viral replication, various high-quality protein crystal structures, and as a basis for computationally screening for compounds with improved inhibitory activity, bioavailability, and ADMETox properties. The ChEMBL and PubChem database contains experimental data from screening small molecules against SARS-CoV-2 3CLpro, which expands the opportunity to learn the pattern and design a computational model that can predict the potency of any drug compound against coronavirus before in-vitro and in-vivo testing. In this study, Utilizing several descriptors, we evaluated 27 machine learning classifiers. We also developed a neural network model that can correctly identify bioactive and inactive chemicals with 91% accuracy, on CheMBL data and 93% accuracy on combined data on both CheMBL and Pubchem. The F1-score for inactive and active compounds was 93% and 94%, respectively. SHAP (SHapley Additive exPlanations) on XGB classifier to find important fingerprints from the PaDEL descriptors for this task. The results indicated that the PaDEL descriptors were effective in predicting bioactivity, the proposed neural network design was efficient, and the Explanatory factor through SHAP correctly identified the important fingertips. In addition, we validated the effectiveness of our proposed model using a large dataset encompassing over 100,000 molecules. This research employed various molecular descriptors to discover the optimal one for this task. To evaluate the effectiveness of these possible medications against SARS-CoV-2, more in-vitro and in-vivo research is required.

Transcriptomic Profiling of Influenza A Virus-Infected Mouse Lung at Recovery Stage Using RNA Sequencing.

Influenza A virus (IAV) is known to cause mild to severe respiratory illness. Under some conditions, the infection can lead to pneumonia (viral or bacterial), acute respiratory distress syndrome, and other complications that can be fatal, especially in vulnerable populations such as the elderly, young children, and individuals with underlying health conditions. Despite previous studies, little is known about the host immune response and neuroimmune interactions in IAV infection. Using RNA sequencing, we performed transcriptomic analysis of murine lung tissue 21 days post infection (dpi) with IAV (H1N1) in order to find the differentially expression genes (DEGs) related to the host immune response and neuroimmune interactions inside the lung during recovery. Among 792 DEGs, 434 genes were up-regulated, whereas 358 genes were down-regulated. The most prominent molecular functions of the up-regulated genes were related to the immune response and tissue repair, whereas a large proportion of the down-regulated genes were associated with neural functions. Although further molecular/functional studies need to be performed for these DEGs, our results facilitate the understanding of the host response (from innate immunity to adaptive immunity) and neuroimmune interactions in infected lungs at the recovery stage of IAV infection. These genes might have potential uses as mechanistic/diagnostic biomarkers and represent possible targets for anti-IAV therapies.

Global Burden of Lumpy Skin Disease, Outbreaks, and Future Challenges.

Lumpy skin disease (LSD), a current global concern, causes economic devastation in livestock industries, with cattle and water buffalo reported to have higher morbidity and lower mortality rates. LSD is caused by lumpy skin disease virus (LSDV), a member of the Poxviridae family. It is an enzootic, rapidly explorative and sometimes fatal infection, characterized by multiple raised nodules on the skin of infected animals. It was first reported in Zambia in 1929 and is considered endemic in Africa south of the Sahara desert. It has gradually spread beyond Africa into the Middle East, with periodic occurrences in Asian and East European countries. Recently, it has been spreading in most Asian countries including far East Asia and threatens incursion to LSD-free countries. Rapid and accurate diagnostic capabilities, virus identification, vaccine development, vector control, regional and international collaborations and effective biosecurity policies are important for the control, prevention, and eradication of LSD infections. This review critically evaluates the global burden of LSD, the chronological historical outbreaks of LSD, and future directions for collaborative global actions.

Facile acid fermentation extraction of silkworm pupae oil and evaluation of its physical and chemical properties for utilization as edible oil.

Considering the increasing demand for edible oil in recent times, their price in the world market is becoming skyrocketing. In this research, we produced cost-effective edible oil from desilked silkworm pupae (Bombyx mori) applying a facile acid fermentation process, for the first time. The extraction was performed using two different types of organic acids, 3% of each acetic and citric acid. The yield of the extracted oil was 3.52 ± 0.23% from fresh silkworm pupae. The produced oil was then characterized physically and chemically to know its suitability to be used as edible oil. The oil was found with a low peroxide and acid value of 4.82 meq/kg and 1.35 mg KOH/g oil, respectively, and comprised of different fatty acids, in which palmitic acid (32.04%) and oleic acid (34.62%) were in large portions among the total fatty acids. Additionally, the extracted oil included linoleic, α-linolenic, and dihomo-gamma-linolenic acid which have health benefits. The oil was rich with minerals such as Iron, Sodium, Potassium, Calcium, Magnesium, Zinc, and Phosphorus with a negligible concentration of toxic elements such as Manganese, Cobalt, Nickel, Copper, Lead, Cadmium, Chromium, Arsenic, and Silver, indicating a good nutritive value of the extracted oil. Overall, the outcomes of all the characterizations showed that the extracted oil could be used as good edible oil and the corresponding acid fermentation extraction process has the potential to be used as an effective oil extraction method for silkworm pupae.