Browse publications by year: 2023

Fulltext Effects of internal and external corporate social responsibility on employee job satisfaction during a pandemic: A medical device industry perspective

Cheah JSS, Lim KH

Eur Manag J, 2023 Apr 08.
PMID: 37362857 DOI: 10.1016/j.emj.2023.04.003

The outbreak of the COVID-19 pandemic has dramatically changed human lifestyles and contributed to the creation of a new normal in the business environment. This study examines the direct and indirect impacts of internal and external corporate social responsibility (CSR) practices on employee job satisfaction through organisational identification, conditional on employee age. A total of 236 valid responses were received from eight multinational medical device manufacturers in Malaysia. Partial least squares and PROCESS algorithms were employed to assess the hypothesised interactions between the predictors and criterion variables. The empirical results showed that internal CSR (i.e., CSR to employee) could significantly drive a greater sense of belonging and work satisfaction. Surprisingly, however, external CSR (i.e., CSR to community) negatively affects job fulfilment in the medical devices industry during the pandemic. Nevertheless, the findings also showed that ongoing CSR activities in the community could build organisational identification and subsequently improve job satisfaction. Conversely, CSR to environment did not statistically influence job satisfaction, either directly or indirectly. The mediating effects of organisational identification were not associated with employee age. This study provides a practical framework for effective CSR strategies amid the pandemic that can help organisations align with social responsibility, enhance their reputation, and contribute to society.
Fulltext Applications of AI in oil and gas projects towards sustainable development: a systematic literature review

Waqar A, Othman I, Shafiq N, Mansoor MS

Artif Intell Rev, 2023 Mar 23.
PMID: 37362898 DOI: 10.1007/s10462-023-10467-7

Oil and gas construction projects are critical for meeting global demand for fossil fuels, but they also present unique risks and challenges that require innovative construction approaches. Artificial Intelligence (AI) has emerged as a promising technology for tackling these challenges, and this study examines its applications for sustainable development in the oil and gas industry. Using a systematic literature review (SLR), this research evaluates research trends from 2011 to 2022. It provides a detailed analysis of how AI suits oil and gas construction. A total of 115 research articles were reviewed to identify original contributions, and the findings indicate a positive trend in AI research related to oil and gas construction projects, especially after 2016. The originality of this study lies in its comprehensive analysis of the latest research on AI applications in the oil and gas industry and its contribution to developing recommendations for improving the sustainability of oil and gas projects. This research's originality is in providing insight into the most promising AI applications and methodologies that can help drive sustainable development in the oil and gas industry.
Fulltext A bibliometric analysis of sustainable development goals (SDGs): a review of progress, challenges, and opportunities

Mishra M, Desul S, Santos CAG, Mishra SK, Kamal AHM, Goswami S, et al.

Environ Dev Sustain, 2023 May 07.
PMID: 37362966 DOI: 10.1007/s10668-023-03225-w

The Sustainable Development Goals (SDGs) are a global appeal to protect the environment, combat climate change, eradicate poverty, and ensure access to a high quality of life and prosperity for all. The next decade is crucial for determining the planet's direction in ensuring that populations can adapt to climate change. This study aims to investigate the progress, challenges, opportunities, trends, and prospects of the SDGs through a bibliometric analysis from 2015 to 2022, providing insight into the evolution and maturity of scientific research in the field. The Web of Science core collection citation database was used for the bibliometric analysis, which was conducted using VOSviewer and RStudio. We analyzed 12,176 articles written in English to evaluate the present state of progress, as well as the challenges and opportunities surrounding the SDGs. This study utilized a variety of methods to identify research hotspots, including analysis of keywords, productive researchers, and journals. In addition, we conducted a comprehensive literature review by utilizing the Web of Science database. The results show that 31% of SDG-related research productivity originates from the USA, China, and the UK, with an average citation per article of 15.06. A total of 45,345 authors around the world have contributed to the field of SDGs, and collaboration among authors is also quite high. The core research topics include SDGs, climate change, Agenda 2030, the circular economy, poverty, global health, governance, food security, sub-Saharan Africa, the Millennium Development Goals, universal health coverage, indicators, gender, and inequality. The insights gained from this analysis will be valuable for young researchers, practitioners, policymakers, and public officials as they seek to identify patterns and high-quality articles related to SDGs. By advancing our understanding of the subject, this research has the potential to inform and guide future efforts to promote sustainable development. The findings indicate a concentration of research and development on SDGs in developed countries rather than in developing and underdeveloped countries.
Fulltext Spatial pattern and influencing factors of tourism based on POI data in Chengdu, China

Liang W, Ahmad Y, Mohidin HHB

Environ Dev Sustain, 2023 Mar 27.
PMID: 37362977 DOI: 10.1007/s10668-023-03138-8

Based on the analysis of the spatial distribution characteristics and influencing factors of 2879 attractions POI in Chengdu, this paper studies the spatial distribution types, spatial concentration, and equilibrium of attractions by using standard deviation ellipse, geographic concentration index, and kernel density estimation. Buffer analysis, near analysis, correlation analysis, and grey relation analysis are used to study the influencing factors of tourism in Chengdu. The results show that: (1) The overall attractions POI in Chengdu is in an east-west direction, and except for other types of attractions POI, the remaining types are also in an east-west direction. (2) The spatial agglomeration areas of different types of attractions POI in Chengdu were quite different. Among them, parks and city squares were mainly concentrated in the central urban areas, namely Jinjiang, Qingyang, Jinniu, Wuhou, and Chenghua, forming a prominent gathering area. (3) There were differences in the influence degree of each factor on the spatial distribution of attractions POI. Topography and drainage, transportation, tourist source market, and other factors significantly correlated with the distribution of attractions, which were the main factors affecting the spatial distribution of attractions. Industrial development and economic population were also important factors affecting the distribution of attractions. Tourism is an important thrust for urban development. The study of the spatial distribution of tourism and its influencing factors has clear guiding significance for later tourism development, which can help optimize the integration of tourism resources, promote the cooperation of regional tourism development and provide a basis for decision-making for tourism development.
Fulltext Spatial prediction of soil erosion risk using knowledge-driven method in Malaysia's Steepland Agriculture Forested Valley

Nasir Ahmad NSB, Mustafa FB, Muhammad Yusoff SY

Environ Dev Sustain, 2023 Apr 21.
PMID: 37362990 DOI: 10.1007/s10668-023-03251-8

Soil is a fundamental resource with its value vital to the world's ecosystem. Due to the fact that soil is one of the bases of all terrestrial life, humans cannot survive without it. However, soil erosion has jeopardized soil sustainability and affected the environmental quality, leaving a bad impact if these issues were not tackled at an earlier phase. Many research has been done to predict soil erosion susceptibility areas using different methods. This research aims to classify the contributing factors of soil erosion according to the risk and generate a soil erosion risk prediction map in Cameron Highlands. Thus, this research focuses on a knowledge-driven method that uses Analytical Hierarchy Process (AHP) technique to achieve the objectives. This technique consists of weighing the factors adopted by comparing pairs of factors that control erosion in this area through experts' opinions. 15 factors have been chosen to build the prediction map. Result shows that rainfall erosivity is the main factor contributing to soil erosion in Cameron Highlands which is 0.110, followed by land use (0.095), slope steepness (0.089), soil texture (0.079), NDVI (0.079), TWI (0.072), slope length (0.065), slope aspect (0.064), slope altitude (0.062), SPI (0.061), lithology (0.060), slope curvature (0.054), drainage density (0.049), distance to road (0.029) and distance to stream (0.025). The west part of the study area was exposed to a high risk of soil erosion. This research will give the decision-makers, policymakers and planners insight into minimizing the soil erosion problem and suggest better precautions and solutions to overcome this severe environmental problem in the more advanced phase.
Fulltext Motivators and barriers of circular economy business model adoption and its impact on sustainable production in Malaysia

Ting LS, Zailani S, Sidek NZM, Shaharudin MR

Environ Dev Sustain, 2023 May 23.
PMID: 37362996 DOI: 10.1007/s10668-023-03350-6

The circular economy concept is popular among developed countries contributing to sustainable production, efficient resource utilization, a new economic model, and higher skill job creation. In production and consumption, it is inevitable in our modern life that we are used to the traditional linear economy cradle-to-cradle model. With the gap in developing countries within the Southeast Asia region, this research aims to understand the motivators and barriers to circular economy business model adoption among the manufacturing firms in Malaysia. Subsequently, the impact of sustainable production will be studied based on the circular economy business model adoption. Using the Theory of Planned Behavior and Partial Least Squares Structural Equation Modeling, this study assesses the responses of 102 respondents from various industries with environmental management systems within Malaysia. Survey-based primary data was gathered to understand motivators and barriers that negatively influence the circular economy business adoption, affecting sustainable production. The findings show that motivators have a positive impact while barriers have a negative impact on circular economy business model adoption. Apart from the barriers and motivators, the research also assesses the level of circular economy adoption among manufacturing firms with certified environmental management systems. This implies a general overview for manufacturing firms in Malaysia regarding circular economy adoption and contributes to the studies done in developing nations. In conclusion, motivators positively impact the adoption of the circular economy business model, while barriers have a negative effect. In addition, adopting the circular economy model has a positive relationship with sustainable production.
Fulltext Green finance in circular economy: a literature review

Kumar B, Kumar L, Kumar A, Kumari R, Tagar U, Sassanelli C

Environ Dev Sustain, 2023 May 17.
PMID: 37362997 DOI: 10.1007/s10668-023-03361-3

Developing markets are using sustainable development potential to reach zero-carbon goals. Due to the limitation of natural resources, companies need to use environmentally friendly manufacturing to develop a circular economy (CE). Green finance (GF) and the CE are linked in a systematic and complex approach; therefore, it was essential to employ the coupling coordination-level framework to explain their relationship and feedback. Any study linking green financing and CE together has been found. The objective of this research is to explore this twofold domain and determine its main characteristics. To address this objective, a comprehensive review of the literature was conducted, supplemented by a bibliometric analysis. The results confirm that GF has the potential to help society, sustainability, and the prevention to climate shifts, investing in the CE. There are many hurdles to overcome, including inadequate knowledge about CE and GF, ambiguous definitions, a lack of coherence between legal frameworks on CE and green financing, unclear laws, and a lack of financially viable motivation for investors and financial institutions that are ready to promote in sustainability. This study explores CE and GF domains. Managers may readily increase their understanding of methods, strategies, and technical solutions beneficial to assist their operations toward a green economy depending on various CE and GF elements. Finally, based on a categorization of GF types, the assessment identifies future investment potential consequences of green financing in the CE.
Fulltext Editorial: Mental health issues in Southeast Asia regions: looking back and moving forward

Tan KA, Keng SL, Abu Talib M

Front Psychiatry, 2023;14:1229079.
PMID: 37363176 DOI: 10.3389/fpsyt.2023.1229079
Fulltext Use of saliva as an alternative diagnostic method for diagnosis of COVID-19

Ganie MW, Nainggolan IRA, Bestari R, Hazidar AH, Hasibuan M, Siregar J, et al.

IJID Reg, 2023 May 04.
PMID: 37363193 DOI: 10.1016/j.ijregi.2023.03.011

BACKGROUND: Mass population testing has been recommended to contain the spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. However, the use of nasopharyngeal swab specimens has caused many logistic challenges. This study investigated the sensitivity and specificity of saliva as a non-invasively-obtained specimen for molecular detection of SARS-CoV-2 RNA.
METHODS: In total, 153 patients with confirmed coronavirus disease 2019 (COVID-19) who had been admitted to the regional referral hospital or who self-isolated at home were included in this study. Nasopharyngeal swab specimens and saliva samples were collected on the same day, and were tested for SARS-CoV-2 infection using reverse transcriptase polymerase chain reaction.
RESULTS: The sensitivity and specificity of saliva samples were 81.5% and 76.4%, respectively, in cases that had been confirmed as COVID-19 using nasopharyngeal swab samples. Positive predictive values and negative predictive values were 92.3% and 54.1%, respectively. The highest detection rates were found among samples collected 4-7 days since symptom onset.
CONCLUSION: Saliva samples showed comparable performance to nasopharyngeal swab specimens for the diagnosis of COVID-19 in adults. The performance of saliva as a diagnostic specimen for COVID-19 testing is particularly significant during the first week of symptoms.
Fulltext Characterization of crude glycerol and glycerol pitch from palm-based residual biomass

Armylisas AHN, Hoong SS, Tuan Ismail TNM

Biomass Convers Biorefin, 2023 Mar 02.
PMID: 37363204 DOI: 10.1007/s13399-023-04003-4

Crude glycerol (CG) and glycerol pitch (GP) are highly alkaline residues from biodiesel and oleochemical plants, respectively, and have organic content which incurs high disposal cost and poses an environmental threat. Characterization of these residues for composition and properties could provide insight into their quality for proper disposal and can help the biodiesel industry to adopt more sustainable practices, such as reducing waste and improving the efficiency of the production process, hence minimizing the impact of the biodiesel supply chain to the environment. These data also allow the identification and exploration of new ways for their utilization and transformation into highly value-added products. In this study, we evaluated four CG samples (B, C, D, and E) and two GP samples (F and G) obtained from Malaysian palm oil refineries, and the results were compared with pure glycerol (A). Spectroscopic analysis was performed using FTIR, 1H-, and 13C-NMR. All samples had similar density to A (1.26 g/cm3), except for F (1.31 g/cm3), while the density for E and G could not be determined due to their physical states. The pH and viscosity largely varied in the range of 7.26-11.89 and 43-225 cSt, respectively. The glycerol content of CG (B, C, D, and E) was high and consistent (81.7-87.3%) whereas GP F and G had 71.5 and 63.9% glycerol content, respectively. Major contaminants in CG and GP were water and matter organic non-glycerol (MONG), respectively. The water, ash, soap, and salt content were considerably low, which varied from 3.4 to 14.1%, 3.9 to 13.0%, 0.1 to 5.7%, and 4.1 to 9.2% respectively. Thermal analysis of CG and GP exhibited four phases of decomposition attributed to the impurities compared to the single phase in A. All samples had calorific values lower than A (18.1 MJ/kg) between 9.0 and 17.7 MJ/kg. Based on the results, CG and GP have high glycerol content which reveals their potential to be used as feedstock in bioconversion and chemical or thermal treatment while impurities may be removed by pre-treatment if required. As palm oil is one of the main feedstocks for the oleochemical industry, this work underlines the importance of characterization of the residue generated to provide additional data and information on palm-based agricultural industry wastes, minimize the impact of palm oil supply chain on the environment, and explore its potential usage for value-addition.
SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13399-023-04003-4.
Fulltext Diet change and sustainability in Indigenous areas: characteristics, drivers, and impacts of diet change in Gunayala, Panama

Lam RD, Huynh LTM, Lozano Lazo DP, Gasparatos A

Sustain Sci, 2023 May 11.
PMID: 37363303 DOI: 10.1007/s11625-023-01325-0

Many Indigenous communities around the world have been experiencing rapid and profound diet changes. This case report uses a Sustainability Science lens to understand the characteristics of diet change in Indigenous Gunas communities of Panama, as well as its drivers and sustainability impacts. We use primary information collected through interviews with 30 experts and 232 household surveys in three Gunas islands characterised by different levels of development, western influence, and cultural erosion. We observe a rapid westernization of diets that has been mainly driven by closer interaction with tourists and the Panamanian society, as well as broader development processes. However, this diet change has a series of intersecting sustainability impacts related to food security, health, and socio-cultural and environmental change. It is necessary to understand the intersection of these phenomena when designing programs and interventions that seek to prevent or mitigate negative diet changes in Gunayala, and other Indigenous contexts more broadly.
SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11625-023-01325-0.
Fulltext Valorization of Salmo salar Skin Waste for the Synthesis of Angiotensin Converting Enzyme-1 (ACE1) Inhibitory Peptides

Munawaroh HSH, Gumilar GG, Khoiriah SF, Nindya FS, Berliana N, Aisyah S, et al.

Waste Biomass Valorization, 2023 May 03.
PMID: 37363337 DOI: 10.1007/s12649-023-02141-4

One of potential inhibitors which is widely used for the clinical treatment of COVID-19 in comorbid patients is Angiostensin Converting Enzyme-1 (ACE1) inhibitor. A safer peptide-based ACE1 inhibitor derived from salmon skin collagen, that is considered as the by-product of the fish processing industry have been investigated in this study. The inhibitory activity against ACE1 was examined using in vitro and in silico methods. In vitro analysis includes the extraction of acid-soluble collagen, characterization using FTIR, Raman, UV-Vis, XRD, cytotoxicity assay, and determination of inhibition against ACE1. In silico method visualizes binding affinity, molecular interaction, and inhibition type of intact collagen and active peptides derived from collagen against ACE1 using molecular docking. The results of FTIR spectra detected amide functional groups (A, B, I, II, III) and imine proline/hydroxyproline, while the results of Raman displayed peak absorption of amide I, amide III, proline/hydroxyproline ring, phenylalanine, and protein backbone. Furthermore, UV-Vis spectra showed typical collagen absorption at 230 nm and based on XRD data, the chain types in the samples were α-helix. ACE1 inhibition activity was obtained in a concentration-dependent manner where the highest was 82.83% and 85.84% at concentrations of 1000, and 2000 µg/mL, respectively, and showed very low cytotoxicity at the concentration less than 1000 µg/mL. In silico study showed an interaction between ACE1 and collagen outside the active site with the affinity of - 213.89 kcal/mol. Furthermore, the active peptides of collagen displayed greater affinity compared to lisinopril, namely HF (His-Phe), WYT (Trp-Tyr-Thr), and WF (Trp-Phe) of - 11.52; - 10.22; - 9.58 kcal/mol, respectively. The salmon skin-derived collagen demonstrated ACE1 inhibition activity with a non-competitive inhibition mechanism. In contrast, the active peptides were predicted as potent competitive inhibitors against ACE1. This study indicated that valorization of fish by-product can lead to the production of a promising bioactive compound to treat COVID-19 patient with diabetic comorbid.
Fulltext Encapsulation of Hydrophobic Apigenin into Small Unilamellar Liposomes Coated with Chitosan Through Ethanol Injection and Spray Drying

Ang SS, Thoo YY, Siow LF

Food Bioproc Tech, 2023 Jun 13.
PMID: 37363383 DOI: 10.1007/s11947-023-03140-y

Despite the multiple health benefits, natural flavonoid apigenin has poor aqueous solubility that restricts its delivery in foods. This study investigated the potential of spray-dried chitosan-coated liposomes prepared from scalable methods for the food industry as the delivery carriers for apigenin. Apigenin-loaded small unilamellar liposomes produced from ethanol injection had an encapsulation efficiency of 74.88 ± 5.31%. They were electrostatically stabilised via chitosan coating (0.25% w/v) and spray-dried. Spray-dried chitosan-coated apigenin liposomes (SCAL) exhibited the following powder characteristics: yield 66.62 ± 3.08%, moisture content 4.33 ± 0.56%, water activity 0.2242 ± 0.0548, particle size 10.97 ± 1.55 μm, nearly spherical morphology with wrinkles and dents under microscopic observation. Compared with the unencapsulated apigenin, SCAL demonstrated improved aqueous solubility (10.22 ± 0.18 mg/L), higher antioxidant capacity, and stability against simulated gastrointestinal digestion. The chitosan coating gave a slower in-vitro release of apigenin in SCAL (77.0 ± 6.2%) than that of uncoated apigenin liposomes (94.0 ± 5.3%) at 12 h. The apigenin release kinetics from SCAL could be represented by the Korsmeyer-Peppas model (R2 = 0.971). These findings suggest that SCAL could be a promising delivery system of apigenin for functional food applications.
Fulltext Prospects of evolution-based artificial intelligence models in genome-wide studies to stratify genetic risk variants in nonalcoholic fatty liver disease

Huang H, Awuah WA, Garg T, Ng JC, Mehta A, Ramamoorthy K, et al.

Ann Med Surg (Lond), 2023 Jun;85(6):2743-2748.
PMID: 37363524 DOI: 10.1097/MS9.0000000000000743

The emergence of genome-wide association studies (GWAS) has identified genetic traits and polymorphisms that are associated with the progression of nonalcoholic fatty liver disease (NAFLD). Phospholipase domain-containing 3 and transmembrane 6 superfamily member 2 are genes commonly associated with NAFLD phenotypes. However, there are fewer studies and replicability in lesser-known genes such as LYPLAL1 and glucokinase regulator (GCKR). With the advent of artificial intelligence (AI) in clinical genetics, studies have utilized AI algorithms to identify phenotypes through electronic health records and utilize convolution neural networks to improve the accuracy of variant identification, predict the deleterious effects of variants, and conduct phenotype-to-genotype mapping. Natural language processing (NLP) and machine-learning (ML) algorithms are popular tools in GWAS studies and connect electronic health record phenotypes to genetic diagnoses using a combination of international classification disease (ICD)-based approaches. However, there are still limitations to machine-learning - and NLP-based models, such as the lack of replicability in larger cohorts and underpowered sample sizes, which prevent the accurate prediction of genetic variants that may increase the risk of NAFLD and its progression to advanced-stage liver fibrosis. This may be largely due to the lack of understanding of the clinical consequence in the majority of pathogenic variants. Though the concept of evolution-based AI models and evolutionary algorithms is relatively new, combining current international classification disease -based NLP models with phylogenetic and evolutionary data can improve prediction accuracy and create valuable connections between variants and their pathogenicity in NAFLD. Such developments can improve risk stratification within clinical genetics and research while overcoming limitations in GWAS studies that prevent community-wide interpretations.
Fulltext Percutaneous coronary intervention versus coronary artery bypass grafting among patients with left ventricular systolic dysfunction: a systematic review and meta-analysis

Jaiswal V, Ang SP, Shrestha AB, Joshi A, Ishak A, Chia JE, et al.

Ann Med Surg (Lond), 2023 Jun;85(6):2849-2857.
PMID: 37363575 DOI: 10.1097/MS9.0000000000000634

Current guidelines have shown the superiority of coronary artery bypass grafting (CABG) over medical therapy. However, there is a paucity of data evaluating the optimal revascularization strategy in patients with ischemic left ventricular systolic dysfunction (LVSD).
OBJECTIVE: The authors aimed to evaluate the clinical outcomes of postpercutaneous coronary intervention (PCI) and CABG among patients with LVSD.
METHODS: The authors performed a systematic literature search using the PubMed, Embase, Scopus, and the Cochrane Libraries for relevant articles from inception until 30 November 2022. Outcomes were reported as pooled odds ratio (OR), and their corresponding 95% CI using STATA (version 17.0, StataCorp).
RESULTS: A total of 10 studies with 13 324 patients were included in the analysis. The mean age of patients in PCI was 65.3 years, and 64.1 years in the CABG group. The most common comorbidities included: HTN (80 vs. 78%) and DM (49.2 vs. 49%). The mean follow-up duration was 3.75 years. Compared with CABG, the PCI group had higher odds of all-cause mortality (OR 1.15, 95% CI 1.01-1.31, P=0.03), repeat revascularization (OR 3.57, 95% CI 2.56-4.97, P<0.001), MI (OR 1.92, 95% CI 1.01-3.86, P=0.048) while the incidence of cardiovascular mortality (OR 1.23, 95% CI 0.98-1.55, P=0.07), stroke (OR 0.73 95% CI: 0.51-1.04, P=0.08), major adverse cardiovascular and cerebrovascular events (OR 1.36, 95% CI 0.99-1.87, P=0.06), and ventricular tachycardia (OR 0.79, 95% CI 0.22-2.86, P=0.72) was comparable between both the procedures.
CONCLUSION: The results of this meta-analysis suggest that CABG is superior to PCI for patients with LVSD. CABG was associated with a lower risk of all-cause mortality, repeat revascularization, and incidence of myocardial infarction compared with PCI in patients with LVSD.
Fulltext Knowledge of mpox and its determinants among the healthcare personnel in Arabic regions: A multi-country cross-sectional study

Swed S, Bohsas H, Patwary MM, Alibrahim H, Rakab A, Nashwan AJ, et al.

New Microbes New Infect, 2023 Sep;54:101146.
PMID: 37363720 DOI: 10.1016/j.nmni.2023.101146

BACKGROUND & AIM: The monkeypox virus (MPXV), an Orthopoxvirus family member, is the zoonotic agent that causes mpox (formerly known as monkeypox). The ongoing mpox pandemic has caused cases across continents involving 110 countries. This study aimed to assess mpox knowledge and its determinants among healthcare personnel.
METHODS: This cross-sectional study was conducted from June 6 to June 25, 2022, among 17 Arab countries. The self-administered questionnaire consists of 53 questions assessing the knowledge about the monkeypox virus.
RESULTS: In total, 5874 medical students and clinical doctors from 17 Arab countries participated in this study. Only 13.8% (n = 812) of respondents have ever received information about mpox during their studies in medicine. The mean knowledge score was 13.84, and the median score was 15 (range 1-34). More than half (51.3%, n = 3012) have heard about mpox before. A low proportion of the participants had a good level of knowledge on mpox. Only 11.7% of respondents had correctly identified the natural host and the incubation period of mpox. More than half (58.9%) were aware of the signs and symptoms of mpox. Few respondents (28%) believed that mpox and smallpox have similar signs and symptoms. Specialist doctors had higher knowledge of mpox (AOR = 2.96, 95% CI = 2.24-3.92, p
Fulltext Undergraduate Students' Profiles of Cognitive Load in Augmented Reality-Assisted Science Learning and Their Relation to Science Learning Self-efficacy and Behavior Patterns

Lin XF, Wong SY, Zhou W, Shen W, Li W, Tsai CC

Int J Sci Math Educ, 2023 May 04.
PMID: 37363784 DOI: 10.1007/s10763-023-10376-9

Research evidence indicated that a specific type of augmented reality-assisted (AR-assisted) science learning design or support might not suit or be effective for all students because students' cognitive load might differ according to their experiences and individual characteristics. Thus, this study aimed to identify undergraduate students' profiles of cognitive load in AR-assisted science learning and to examine the role of their distinct profiles in self-efficacy together with associated behavior patterns in science learning. After ensuring the validity and reliability of each measure, a latent profile analysis confirmed that 365 Chinese undergraduates carried diverse dimensions of cognitive load simultaneously. The latent profile analysis findings revealed four fundamental profiles: Low Engagement, Immersive, Dabbling, and Organized, characterized as carrying various respective cognitive loads. The multivariate analysis of variance findings revealed different levels of the six AR science learning self-efficacy dimensions across profiles. Low Engagement students displayed the lowest self-efficacy among all dimensions. Organized students recorded better conceptual understanding and higher-order cognitive skills than Dabbling ones. Students with the Immersive profile had the highest science learning self-efficacy. The lag sequential analysis results showed significant differences in behavior patterns among profiles. Among them, profiles with social interaction, test, and reviewing feedback behavior had a significantly higher score for self-efficacy than those patterns mainly based on test learning and resource visits. This finding provides a unified consideration of students' diverse profiles and can inform interventions for effective design of AR-assisted science learning to match appropriate strategies to facilitate the science learning effect.
Fulltext Perception of COVID-19 vaccination among Indian Twitter users: computational approach

Davidson PD, Muniandy T, Karmegam D

J Comput Soc Sci, 2023 Mar 28.
PMID: 37363805 DOI: 10.1007/s42001-023-00203-0

Vaccination has been a hot topic in the present COVID-19 context. The government, public health stakeholders and media are all concerned about how to get the people vaccinated. The study was intended to explore the perception and emotions of the Indians citizens toward COVID-19 vaccine from Twitter messages. The tweets were collected for the period of 6 months, from mid-January to June, 2021 using hash-tags and keywords specific to India. Topics and emotions from the tweets were extracted using Latent Dirichlet Allocation (LDA) method and National Research Council (NRC) Lexicon, respectively. Theme, sentiment and emotion wise engagement and reachability metrics were assessed. Hash-tag frequency of COVID-19 vaccine brands were also identified and evaluated. Information regarding 'Co-WIN app and availability of vaccine' was widely discussed and also received highest engagement and reachability among Twitter users. Among the various emotions, trust was expressed the most, which highlights the acceptance of vaccines among the Indian citizens. The hash-tags frequency of vaccine brands shows that Covishield was popular in the month of March 2021, and Covaxin in April 2021. The results from the study will help stakeholders to efficiently use social media to disseminate COVID-19 vaccine information on popular concerns. This in turn will encourage citizens to be vaccinated and achieve herd immunity. Similar methodology can be adopted in future to understand the perceptions and concerns of people in emergency situations.
SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42001-023-00203-0.
Application of Conductive Hydrogels on Spinal Cord Injury Repair: A Review

Shahemi NH, Mahat MM, Asri NAN, Amir MA, Ab Rahim S, Kasri MA

ACS Biomater Sci Eng, 2023 Jul 10;9(7):4045-4085.
PMID: 37364251 DOI: 10.1021/acsbiomaterials.3c00194

Spinal cord injury (SCI) causes severe motor or sensory damage that leads to long-term disabilities due to disruption of electrical conduction in neuronal pathways. Despite current clinical therapies being used to limit the propagation of cell or tissue damage, the need for neuroregenerative therapies remains. Conductive hydrogels have been considered a promising neuroregenerative therapy due to their ability to provide a pro-regenerative microenvironment and flexible structure, which conforms to a complex SCI lesion. Furthermore, their conductivity can be utilized for noninvasive electrical signaling in dictating neuronal cell behavior. However, the ability of hydrogels to guide directional axon growth to reach the distal end for complete nerve reconnection remains a critical challenge. In this Review, we highlight recent advances in conductive hydrogels, including the incorporation of conductive materials, fabrication techniques, and cross-linking interactions. We also discuss important characteristics for designing conductive hydrogels for directional growth and regenerative therapy. We propose insights into electrical conductivity properties in a hydrogel that could be implemented as guidance for directional cell growth for SCI applications. Specifically, we highlight the practical implications of recent findings in the field, including the potential for conductive hydrogels to be used in clinical applications. We conclude that conductive hydrogels are a promising neuroregenerative therapy for SCI and that further research is needed to optimize their design and application.

MeSH terms: Electric Conductivity; Humans; Nerve Regeneration
Effects of R-salbutamol on the inflammatory response and acute lung injury in endotoxemic mice

Beng H, Hu J, Wang S, Liang X, Qin H, Tan W

Int Immunopharmacol, 2023 Aug;121:110482.
PMID: 37364330 DOI: 10.1016/j.intimp.2023.110482

Salbutamol, which consists of an R-isomer and S-isomer, is an effective and widely used β2 adrenoreceptor agonist that may possess anti-inflammatory properties in addition to its bronchodilator activity. Whether the salbutamol R-isomer has advantages over its racemic mixture and effectiveness in treating endotoxemia and endotoxin-induced lung injury has not been well studied. In this study, we investigated the preventive and therapeutic effects of R-salbutamol (R-sal), S-salbutamol (S-sal), and their racemic mixture (Rac-sal) on a mouse model of lipopolysaccharide (LPS)-induced endotoxemia. Dexamethasone (Dex) was used for comparison. The results showed that R-sal markedly improved the 7-day survival rate of endotoxic mice when administered before and after LPS treatment. Dex was toxic and accelerated the death of endotoxic mice when administered before LPS injection. Histological examination of the lungs revealed that the LPS challenge resulted in acute lung damage, including inflammatory cell infiltration, thickened alveolar septa, and congestion. R-sal pre-treatment effectively inhibited these changes, accompanied by markedly reduced lung myeloperoxidase levels, serum cytokine levels, and lactate release, significant restoration of lymphocyte count, and reduction of monocyte count. This may have occurred through inhibition of M1 macrophage inflammatory responses by enhancement of β-arrestin2 expression and suppression of NF-κB activation. Rac-sal exhibited diminished effects compared to that of R-sal, while S-sal showed enhanced release of some inflammatory cytokines. In addition, R-sal pre-treatment showed a better improvement in prognostic pulmonary function on day 4 compared to that by Rac-sal. Collectively, our results indicate the potential benefits of R-sal in regulating inflammatory responses to endotoxemia and endotoxin-induced lung injury.

MeSH terms: Animals; Inflammation/drug therapy; Lipopolysaccharides; Lymphocytes/drug effects; Lymphocytes/metabolism; Mice, Inbred BALB C; Monocytes/drug effects; Monocytes/metabolism; NF-kappa B/metabolism; Lactic Acid/blood; Mice; beta-Arrestin 2/metabolism

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