Browse publications by year: 2023

Aerobic granular sludge development using diatomite for low-strength wastewater treatment

Basri HF, Anuar AN, Halim MHA, Yuzir MA, Muda K, Omoregie AI, et al.

Environ Monit Assess, 2023 Feb 21;195(3):420.
PMID: 36809517 DOI: 10.1007/s10661-023-11028-9

This paper presents an assessment of the start-up performance of aerobic granular sludge (AGS) for the treatment of low-strength (chemical oxygen demand, COD

MeSH terms: Aerobiosis; Environmental Monitoring; Nitrogen; Phosphates; Sewage*; Waste Disposal, Fluid; Water Purification*; Bioreactors
Polycaprolactone-based Nanocarriers Containing 5-fluorouracil as a Therapeutic Guided Drug Delivery Approach for Enhancing Anticancer Activity

Mohammadian S, Khazaei M, Maghami P, Avan A, Rezaei M

Curr Cancer Drug Targets, 2023;23(7):524-533.
PMID: 36809944 DOI: 10.2174/1568009623666230210140212

Nowadays, nano-platforms designed for drug delivery systems (DDSs) such as polymers, liposomes, and micelles have been demonstrated to be clinically efficient. The sustained drug release is one of the advantages of DDSs, especially polymer-based nanoparticles. The formulation could enhance the drug's durability, in which the biodegradable polymers are the most interesting building blocks of DDSs. Nano-carriers could circumvent many issues by localized drug delivery and release via certain internalization routes such as intracellular endocytosis paths and increasing biocompatibility. Polymeric nanoparticles and their nanocomposite are one of the most important classes of materials that can be used for the assembly of nanocarriers that can form complex, conjugated and encapsulated forms. The site-specific drug delivery may arise from the ability of nanocarriers to pass through the biological barrier, their specific interactions with receptors, and passive targeting. The better circulation, uptake, and stability along with targeting attributes lead to lesser side effects and damage to normal cells. Hence, in this review, the most recent achievements on polycaprolactone-based or -modified nanoparticles in drug delivery systems (DDSs) for 5-fluorouracil (5-FU) are presented.

MeSH terms: Drug Carriers; Fluorouracil*; Humans; Polymers; Drug Delivery Systems; Nanoparticles*
Fulltext Diabetes disease prediction system using HNB classifier based on discretization method

Al-Hameli BA, Alsewari AA, Basurra SS, Bhogal J, Ali MAH

J Integr Bioinform, 2023 Mar 01;20(1).
PMID: 36810102 DOI: 10.1515/jib-2021-0037

Diagnosing diabetes early is critical as it helps patients live with the disease in a healthy way - through healthy eating, taking appropriate medical doses, and making patients more vigilant in their movements/activities to avoid wounds that are difficult to heal for diabetic patients. Data mining techniques are typically used to detect diabetes with high confidence to avoid misdiagnoses with other chronic diseases whose symptoms are similar to diabetes. Hidden Naïve Bayes is one of the algorithms for classification, which works under a data-mining model based on the assumption of conditional independence of the traditional Naïve Bayes. The results from this research study, which was conducted on the Pima Indian Diabetes (PID) dataset collection, show that the prediction accuracy of the HNB classifier achieved 82%. As a result, the discretization method increases the performance and accuracy of the HNB classifier.

MeSH terms: Algorithms*; Bayes Theorem; Humans; Data Mining
Fulltext Quality prediction and classification of resistance spot weld using artificial neural network with open-sourced, self-executable and GUI-based application tool Q-Check

Abd Halim S, Manurung YHP, Raziq MA, Low CY, Rohmad MS, Dizon JRC, et al.

Sci Rep, 2023 Feb 21;13(1):3013.
PMID: 36810419 DOI: 10.1038/s41598-023-29906-0

Optimizing Resistance spot welding, often used as a time and cost-effective process in many industrial sectors, is very time-consuming due to the obscurity inherent within process with numerous interconnected welding parameters. Small changes in values will give effect to the quality of welds which actually can be easily analysed using application tool. Unfortunately, existing software to optimize the parameters are expensive, licensed and inflexible which makes small industries and research centres refused to acquire. In this study, application tool using open-sourced and customized algorithm based on artificial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifications (WQC). A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg-Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. All the display and calculation processes are developed and compiled in the form of application tool of graphical user interface (GUI). Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. It is also expected that tool with flexible GUI can be widely used and enhanced by practitioner with minimum knowledge in the domain.
Fulltext Diet Gut Microbiota Axis in Pregnancy: A Systematic Review of Recent Evidence

Kunasegaran T, Balasubramaniam VRMT, Arasoo VJT, Palanisamy UD, Ramadas A

Curr Nutr Rep, 2023 Mar;12(1):203-214.
PMID: 36810808 DOI: 10.1007/s13668-023-00453-4

PURPOSE OF REVIEW: Although gut microbiota have been associated with the etiology of some diseases, the influence of foods on gut microbiota, especially among pregnant women, remains unclear. Hence, a systematic review was performed to investigate the association between diet and gut microbiota and their influence on metabolic health in pregnant women.
RECENT FINDINGS: We performed the systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 protocol to investigate the association between diet and gut microbiota and their influence on metabolic role in pregnant women. Five databases were searched for relevant peer-reviewed articles published in English since 2011. Two-staged screening of 659 retrieved records resulted in the inclusion of 10 studies. The collated findings suggested associations between nutrient intakes and four key microbes: Collinsella, Lachnospira, Sutterella, Faecalibacterium, and the Firmicutes/Bacteroidetes ratio in pregnant women. Dietary intakes in pregnancy were found to modify the gut microbiota and positively influence the cell metabolism in pregnant women. This review, however, emphasizes the importance of conducting well-designed prospective cohorts to investigate the role of changes in dietary intakes within the pregnancy and the influence of such changes on gut microbiota.

MeSH terms: Gastrointestinal Microbiome*; Diet; Female; Humans; Pregnancy; Prospective Studies
Fulltext An augmented Snake Optimizer for diseases and COVID-19 diagnosis

Abu Khurma R, Albashish D, Braik M, Alzaqebah A, Qasem A, Adwan O

Biomed Signal Process Control, 2023 Jul;84:104718.
PMID: 36811003 DOI: 10.1016/j.bspc.2023.104718

Feature Selection (FS) techniques extract the most recognizable features for improving the performance of classification methods for medical applications. In this paper, two intelligent wrapper FS approaches based on a new metaheuristic algorithm named the Snake Optimizer (SO) are introduced. The binary SO, called BSO, is built based on an S-shape transform function to handle the binary discrete values in the FS domain. To improve the exploration of the search space by BSO, three evolutionary crossover operators (i.e., one-point crossover, two-point crossover, and uniform crossover) are incorporated and controlled by a switch probability. The two newly developed FS algorithms, BSO and BSO-CV, are implemented and assessed on a real-world COVID-19 dataset and 23 disease benchmark datasets. According to the experimental results, the improved BSO-CV significantly outperformed the standard BSO in terms of accuracy and running time in 17 datasets. Furthermore, it shrinks the COVID-19 dataset's dimension by 89% as opposed to the BSO's 79%. Moreover, the adopted operator on BSO-CV improved the balance between exploitation and exploration capabilities in the standard BSO, particularly in searching and converging toward optimal solutions. The BSO-CV was compared against the most recent wrapper-based FS methods; namely, the hyperlearning binary dragonfly algorithm (HLBDA), the binary moth flame optimization with Lévy flight (LBMFO-V3), the coronavirus herd immunity optimizer with greedy crossover operator (CHIO-GC), as well as four filter methods with an accuracy of more than 90% in most benchmark datasets. These optimistic results reveal the great potential of BSO-CV in reliably searching the feature space.
Fulltext A successful endoscopic extraction of accidently ingested toothbrush in an adult: a case report

Al-Mulla AE, Buhamad F, Marafie HF, Al Khalifa F

J Surg Case Rep, 2023 Feb;2023(2):rjad044.
PMID: 36811070 DOI: 10.1093/jscr/rjad044

Toothbrush ingestion is a rare phenomenon. It is usually found in psychiatric, elderly and mentally disabled patients. Foreign bodies usually pass spontaneously and uneventfully through the gastrointestinal tract. Nevertheless, larger objects may require early intervention to avoid complications. This report describes the course of treatment for a 25-year-old woman with an accidentally ingested toothbrush.
Validation of AND/ASPEN pediatric malnutrition diagnosis in children admitted to medical wards in two tertiary hospitals in Malaysia

Ong SH, Chen ST, Chee WSS

Nutr Clin Pract, 2023 Aug;38(4):889-898.
PMID: 36811458 DOI: 10.1002/ncp.10971

BACKGROUND: Identification and management of malnutrition among pediatric hospitalized patients is critical for improved clinical outcomes and recovery. This study investigated the use of the Academy of Nutrition and Dietetics and the American Society for Parenteral and Enteral Nutrition (AND/ASPEN) pediatric malnutrition diagnosis in comparison with the Subjective Global Nutritional Assessment (SGNA) tool and single anthropometric indicators (weight, height, body mass index, and mid-upper arm circumference) among hospitalized children.
METHODS: A cross-sectional study was conducted among 260 children admitted to general medical wards. SGNA and anthropometric measurements were used as references. Kappa agreement, diagnostic values, and area under the curve (AUC) were analyzed to evaluate the diagnostic ability of the AND/ASPEN malnutrition diagnosis tool. Logistic binary regression was performed to determine the predictive ability of each malnutrition diagnosis tool on the length of hospital stay.
RESULTS: The AND/ASPEN diagnosis tool detected the highest malnutrition rate (41%) among the hospitalized children in comparison with the reference methods. This tool demonstrated fair specificity of 74% and sensitivity of 70% compared with the SGNA. It obtained a weak agreement in determining the presence of malnutrition by kappa (0.06-0.42) and receiver operating characteristic curve analysis (AUC = 0.54-0.72). The use of the AND/ASPEN tool obtained an odds ratio of 0.84 (95% CI, 0.44-1.61; P = 0.59) in predicting the length of hospital stay.
CONCLUSIONS: The AND/ASPEN malnutrition tool is an acceptable nutrition assessment tool for hospitalized children in general medical wards.

MeSH terms: Child; Cross-Sectional Studies; Humans; Malaysia/epidemiology; Nutritional Status; Nutrition Assessment; Tertiary Care Centers
Mineralogical and chemical characterization of mining waste and utilization for carbon sequestration through mineral carbonation

Molahid VLM, Kusin FM, Syed Hasan SNM

Environ Geochem Health, 2023 Jul;45(7):4439-4460.
PMID: 36811700 DOI: 10.1007/s10653-023-01513-y

Mining activities have often been associated with the issues of waste generation, while mining is considered a carbon-intensive industry that contributes to the increasing carbon dioxide emission to the atmosphere. This study attempts to evaluate the potential of reusing mining waste as feedstock material for carbon dioxide sequestration through mineral carbonation. Characterization of mining waste was performed for limestone, gold and iron mine waste, which includes physical, mineralogical, chemical and morphological analyses that determine its potential for carbon sequestration. The samples were characterized as having alkaline pH (7.1-8.3) and contain fine particles, which are important to facilitate precipitation of divalent cations. High amount of cations (CaO, MgO and Fe2O3) was found in limestone and iron mine waste, i.e., total of 79.55% and 71.31%, respectively, that are essential for carbonation process. Potential Ca/Mg/Fe silicates, oxides and carbonates have been identified, which was confirmed by the microstructure analysis. The limestone waste composed majorly of CaO (75.83%), which was mainly originated from calcite and akermanite minerals. The iron mine waste consisted of Fe2O3 (56.60%), mainly from magnetite and hematite, and CaO (10.74%) which was derived from anorthite, wollastonite and diopside. The gold mine waste was attributed to a lower cation content (total of 7.71%), associated mainly with mineral illite and chlorite-serpentine. The average capacity for carbon sequestration was between 7.73 and79.55%, which corresponds to 383.41 g, 94.85 g and 4.72 g CO2 that were potentially sequestered per kg of limestone, iron and gold mine waste, respectively. Therefore, it has been learned that the mine waste might be utilized as feedstock for mineral carbonation due to the availability of reactive silicate/oxide/carbonate minerals. Utilization of mine waste would be beneficial in light of waste restoration in most mining sites while tackling the issues of CO2 emission in mitigating the global climate change.

MeSH terms: Calcium Carbonate/chemistry; Carbonates/analysis; Gold; Iron; Minerals/chemistry; Carbon Sequestration*
Fulltext Perinatal mental health in Malaysia: understanding the treatment gap and recommendations for the future

Raaj S, Verghese V, Tharmaseelan M, Duffy R, N K Sinnadorai NKST

BJPsych Int, 2023 Feb;20(1):9-12.
PMID: 36812022 DOI: 10.1192/bji.2022.2

Maternal mental health problems are widespread worldwide, especially against the backdrop of population growth. There is an increasing prevalence of perinatal mental illness in low- and middle-income countries, and Malaysia is no exception. Despite significant improvements in the Malaysian mental health system over the past decade, there are substantial gaps in the delivery of perinatal health services in Malaysia. This article seeks to give a general overview of perinatal mental health in Malaysia and provide recommendations for the development of Malaysia's perinatal mental health services.
Fulltext Translation and cross-cultural adaptation of heat strain score index (HSSI) into the Malay language

Lim MC, Lukman KA, Giloi N, Jeffree MS, Saupin SS, Sidek ZN, et al.

PLoS One, 2023;18(2):e0281217.
PMID: 36812176 DOI: 10.1371/journal.pone.0281217

Concerns about the health and safety of working populations as well as preventive actions to reduce heat-related illnesses and fatalities have intensified as global warming and heatwaves continue to rise as a result of climate change. This study aimed to translate and culturally-adapted the translated Malay version of the Heat Strain Score Index (HSSI) questionnaire so that it can be utilized as a screening tool for heat stress among the Malay-speaking outdoor workers. The original English version of HSSI underwent forward-backward translation and was cross-culturally adapted into the Malay language by bilingual translators based on established guidelines. The content validation was reviewed by a six-member expert committee including the representative of outdoor workers. Face validation was carried out among 10 outdoor workers involved with various work tasks. Psychometric analysis was conducted based on a cross-sectional study among 188 workers who were eligible. Exploratory Factor Analysis (EFA) was used for construct validity while internal consistency reliability was performed using Cronbach's alpha. The interclass correlation coefficient (ICC) was used to calculate the test-retest reliability. Both content and face validity were acceptable with the overall content validity index being 1.00, while the universal face validity index was 0.83. The factor analysis using varimax rotation extracted four factors which explained 56.32% of the cumulative percentage of variance and factor loading ranging from 0.415 to 0.804. The internal consistency reliability was acceptable with Cronbach's alpha ranging from 0.705 to 0.758 for all the factors. The overall ICC value was 0.792 (95% CI; 0.764-0.801) which signifies good reliability. The findings from this study indicate that the Malay version of HSSI is a reliable and culturally-adapted instrument. Further validation is needed so that it can be used extensively assess the heat stress among susceptible Malay-speaking outdoor workers in Malaysia who are exposed to hot humid environments.

MeSH terms: Cross-Sectional Studies; Cross-Cultural Comparison*; Humans; Language*; Malaysia; Psychometrics; Surveys and Questionnaires; Reproducibility of Results
Fulltext A new online toolkit to support implementation research to enhance the use of digital innovations to End TB

Veronese V, Miller C, Ogundahunsi O, Den Boon S, Xia YY, Falzon D, et al.

PLOS Digit Health, 2023 Feb;2(2):e0000182.
PMID: 36812644 DOI: 10.1371/journal.pdig.0000182

Digital technologies are playing an increasing role in the global response to tuberculosis (TB), however their effectiveness and impact are often shaped in the context in which they are implemented. Implementation research can help facilitate the effective introduction of digital health technologies in TB programmes. In 2020, the Implementation Research for Digital Technologies and TB online toolkit (IR4DTB) was developed and launched by the Special Programme for Research and Training in Tropical Diseases, and the Global TB Programme at the World Health Organization (WHO), to build local capacity for IR and promote the effective use of digital technologies within TB programmes. This paper describes the development and piloting of the IR4DTB toolkit, a self-learning tool designed for TB programme implementers. The toolkit comprises six modules reflecting key steps of the IR process, practical instructions and guidance on how to complete these steps, and real-word case studies to illustrate key learning points. This paper also describes the launch of the IR4DTB during a five-day training workshop with TB staff from China, Uzbekistan, Pakistan, Malaysia. The workshop included facilitated sessions on the IR4DTB modules, and provided an opportunity for participants to work with facilitators to develop a comprehensive IR proposal addressing an identified challenge related to the implementation and/or scale-up of digital health technologies for TB care in their home country. Post-workshop evaluation revealed high level of satisfaction among participants with the workshop content and format. The IR4DTB toolkit is a replicable model which can be used to strengthen the TB staff capacity to innovate within a culture of continuous collection of evidence. Through continued trainings and adaptation of the toolkit alongside the integration of digital technologies within TB prevention and care, this model has the potential to contribute directly to all components of the End TB Strategy.
Fulltext Natural sources, biological effects, and pharmacological properties of cynaroside

Bouyahya A, Taha D, Benali T, Zengin G, El Omari N, El Hachlafi N, et al.

Biomed Pharmacother, 2023 May;161:114337.
PMID: 36812715 DOI: 10.1016/j.biopha.2023.114337

Cynaroside is a flavonoid, isolated from several species belonging to the Apiaceae, Poaceae, Lamiaceae, Solanaceae, Zingiberaceae, Compositae and other families and it can be extracted from seeds, roots, stems, leaves, barks, flowers, fruits, aerial parts, and the whole plant of these species. This paper discloses the current state of knowledge on the biological/pharmacological effects and mode of action to better understand the numerous health benefits of cynaroside. Several research works revealed that cynaroside could have beneficial effects on various human pathologies. Indeed, this flavonoid exerts antibacterial, antifungal, antileishmanial, antioxidant, hepatoprotective, antidiabetic, anti-inflammatory, and anticancer effects. Additionally, cynaroside exhibits its anticancer effects by blocking MET/AKT/mTOR axis by decreasing the phosphorylation level of AKT, mTOR, and P70S6K. For antibacterial activity, cynaroside reduces biofilm development of Pseudomonas aeruginosa and Staphylococcus aureus. Moreover, the incidence of mutations leading to ciprofloxacin resistance in Salmonella typhimurium was reduced after the treatment with cynaroside. In addition, cynaroside inhibited the production of reactive oxygen species (ROS), which reduced the damage to mitochondrial membrane potential caused by hydrogen peroxide (H2O2). It also enhanced the expression of the anti-apoptotic protein Bcl-2 and lowered that of the pro-apoptotic protein Bax. Cynaroside abrogated the up-regulation of c-Jun N-terminal kinase (JNK) and p53 protein expression triggered by H2O2. All these findings suggest that cynaroside could be used to prevent certain human diseases.

MeSH terms: Anti-Bacterial Agents/pharmacology; Humans; Apoptosis; Reactive Oxygen Species/metabolism; Luteolin/pharmacology; Apoptosis Regulatory Proteins; TOR Serine-Threonine Kinases
Generation of an RNA aptamer against LipL32 of Leptospira isolated by Tripartite-hybrid SELEX coupled with in-house Python-aided unbiased data sorting

Shien Yeoh T, Yusof Hazrina H, Bukari BA, Tang TH, Citartan M

Bioorg Med Chem, 2023 Mar 01;81:117186.
PMID: 36812779 DOI: 10.1016/j.bmc.2023.117186

Leptospirosis is a potentially life-threatening zoonosis caused by pathogenic Leptospira. The major hurdle of the diagnosis of Leptospirosis lies in the issues associated with current methods of detection, which are time-consuming, tedious and the need for sophisticated, special equipments. Restrategizing the diagnostics of Leptospirosis may involve considerations of the direct detection of the outer membrane protein, which can be faster, cost-saving and require fewer equipments. One such promising marker is LipL32, which is an antigen with high amino acid sequence conservation among all the pathogenic strains. In this study, we endeavored to isolate an aptamer against LipL32 protein via a modified SELEX strategy known as tripartite-hybrid SELEX, based on 3 different partitioning strategies. In this study, we also demonstrated the deconvolution of the candidate aptamers by using in-house Python-aided unbiased data sorting in examining multiple parameters to isolate potent aptamers. We have successfully generated an RNA aptamer against LipL32 of Leptospira, LepRapt-11, which is applicable in a simple direct ELASA for the detection of LipL32. LepRapt-11 can be a promising molecular recognition element for the diagnosis of leptospirosis by targeting LipL32.

MeSH terms: Animals; Bacterial Outer Membrane Proteins/metabolism; Humans; Lipoproteins/genetics; Aptamers, Nucleotide*
A computational framework for the multiphysics simulation of microbubble-mediated sonothrombolysis using a forward-viewing intravascular transducer

Tan ZQ, Ooi EH, Chiew YS, Foo JJ, Ng EYK, Ooi ET

Ultrasonics, 2023 May;131:106961.
PMID: 36812819 DOI: 10.1016/j.ultras.2023.106961

Sonothrombolysis is a technique that utilises ultrasound waves to excite microbubbles surrounding a clot. Clot lysis is achieved through mechanical damage induced by acoustic cavitation and through local clot displacement induced by acoustic radiation force (ARF). Despite the potential of microbubble-mediated sonothrombolysis, the selection of the optimal ultrasound and microbubble parameters remains a challenge. Existing experimental studies are not able to provide a complete picture of how ultrasound and microbubble characteristics influence the outcome of sonothrombolysis. Likewise, computational studies have not been applied in detail in the context of sonothrombolysis. Hence, the effect of interaction between the bubble dynamics and acoustic propagation on the acoustic streaming and clot deformation remains unclear. In the present study, we report for the first time the computational framework that couples the bubble dynamic phenomena with the acoustic propagation in a bubbly medium to simulate microbubble-mediated sonothrombolysis using a forward-viewing transducer. The computational framework was used to investigate the effects of ultrasound properties (pressure and frequency) and microbubble characteristics (radius and concentration) on the outcome of sonothrombolysis. Four major findings were obtained from the simulation results: (i) ultrasound pressure plays the most dominant role over all the other parameters in affecting the bubble dynamics, acoustic attenuation, ARF, acoustic streaming, and clot displacement, (ii) smaller microbubbles could contribute to a more violent oscillation and improve the ARF simultaneously when they are stimulated at higher ultrasound pressure, (iii) higher microbubbles concentration increases the ARF, and (iv) the effect of ultrasound frequency on acoustic attenuation is dependent on the ultrasound pressure. These results may provide fundamental insight that is crucial in bringing sonothrombolysis closer to clinical implementation.

MeSH terms: Acoustics; Computer Simulation*; Ultrasonics; Microbubbles*; Endovascular Procedures*
Physicochemical approaches reveal the impact of electrolytes and hydrotropic salt on micellization and phase separation behavior of polymer polyvinyl alcohol and surfactant mixture

Rather SU, Rahman MH, Bamufleh HS, Alhumade H, Taimoor AA, Saeed U, et al.

Int J Biol Macromol, 2023 Apr 30;235:123761.
PMID: 36812977 DOI: 10.1016/j.ijbiomac.2023.123761

The polymer-surfactant mixture has usages in numerous industries mainly in the production of daily used materials. Herein, the micellization and phase separation nature of the sodium dodecyl sulfate (SDS) and TX-100 along with a synthetic water-soluble polymer-polyvinyl alcohol (PVA) have been conducted using conductivity and cloud point (CP) measurement tools. In the case of micellization study of SDS + PVA mixture by conductivity method, the CMC values were obtained to be dependent on the categories and extent of additives as well as temperature variation. Both categories of studies were performed in aq. solutions of sodium chloride (NaCl), sodium acetate (NaOAc), and sodium benzoate (NaBenz) media. The CP values of TX 100 + PVA were decreased and enhanced in simple electrolytes and sodium benzoate media respectively. In all cases, the free energy changes of micellization (∆Gm0) and clouding (∆Gc0) were obtained as negative and positive respectively. The enthalpy (∆Hm0) and entropy (∆Sm0) changes for SDS + PVA system micellization was negative and positive respectively in aq. NaCl and NaBenz media, and in aq. NaOAc medium the ∆Hm0 values were found negative while ∆Sm0 were found negative except at the highest studied temperature (323.15 K). The enthalpy-entropy compensation of both processes was also assessed and described clearly.

MeSH terms: Micelles; Polymers; Polyvinyl Alcohol; Sodium Chloride*; Surface-Active Agents*; Water; Sodium Benzoate
Tree-based machine learning model for visualizing complex relationships between biochar properties and anaerobic digestion

Zhang Y, Feng Y, Ren Z, Zuo R, Zhang T, Li Y, et al.

Bioresour Technol, 2023 Apr;374:128746.
PMID: 36813050 DOI: 10.1016/j.biortech.2023.128746

The ideal conditions for anaerobic digestion experiments with biochar addition are challenging to thoroughly study due to different experimental purposes. Therefore, three tree-based machine learning models were developed to depict the intricate connection between biochar properties and anaerobic digestion. For the methane yield and maximum methane production rate, the gradient boosting decision tree produced R2 values of 0.84 and 0.69, respectively. According to feature analysis, digestion time and particle size had a substantial impact on the methane yield and production rate, respectively. When particle sizes were in the range of 0.3-0.5 mm and the specific surface area was approximately 290 m2/g, corresponding to a range of O content (>31%) and biochar addition (>20 g/L), the maximum promotion of methane yield and maximum methane production rate were attained. Therefore, this study presents new insights into the effects of biochar on anaerobic digestion through tree-based machine learning.

MeSH terms: Machine Learning; Anaerobiosis; Charcoal*; Methane; Bioreactors*
Amyloid precursor protein in Alzheimer's disease

Maurya R, Bhattacharjee G, Khambhati K, Gohil N, Singh P, Mani I, et al.

Prog Mol Biol Transl Sci, 2023;196:261-270.
PMID: 36813361 DOI: 10.1016/bs.pmbts.2022.09.006

Amyloid precursor protein (APP) is a membrane protein expressed in several tissues. The occurrence of APP is predominant in synapses of nerve cells. It acts as a cell surface receptor and plays a vital role as a regulator of synapse formation, iron export and neural plasticity. It is encoded by the APP gene that is regulated by substrate presentation. APP is a precursor protein activated by proteolytic cleavage and thereby generating amyloid beta (Aβ) peptides which eventually form amyloid plaques that accumulate in Alzheimer's disease patients' brains. In this chapter, we highlight basic mechanism, structure, expression patterns and cleavage of amyloid plaques, and its diagnosis and potential treatment for Alzheimer's disease.

MeSH terms: Humans; Membrane Proteins; Amyloid beta-Peptides/metabolism; Plaque, Amyloid
Fulltext Acquired radioresistance in EMT6 mouse mammary carcinoma cell line is mediated by CTLA-4 and PD-1 through JAK/STAT/PI3K pathway

Sham NFR, Hasani NAH, Hasan N, Karim MKA, Fuad SBSA, Hasbullah HH, et al.

Sci Rep, 2023 Feb 22;13(1):3108.
PMID: 36813833 DOI: 10.1038/s41598-023-29925-x

Cancer recurrence is often associated with the acquisition of radioresistance by cancer tissues due to failure in radiotherapy. The underlying mechanism leading to the development of acquired radioresistance in the EMT6 mouse mammary carcinoma cell line and the potential pathway involved was investigated by comparing differential gene expressions between parental and acquired radioresistance cells. EMT6 cell line was exposed to 2 Gy/per cycle of gamma-ray and the survival fraction between EMT6-treated and parental cells was compared. EMT6RR_MJI (acquired radioresistance) cells was developed after 8 cycles of fractionated irradiation. The development of EMT6RR_MJI cells was confirmed with further irradiation at different doses of gamma-ray, and both the survival fraction and migration rates were measured. Higher survival fraction and migration rates were obtained in EMT6RR_MJI cells after exposure to 4 Gy and 8 Gy gamma-ray irradiations compared to their parental cells. Gene expression between EMT6RR_MJI and parental cells was compared, and 16 genes identified to possess more than tenfold changes were selected and validated using RT-PCR. Out of these genes, 5 were significantly up-regulated i.e., IL-6, PDL-1, AXL, GAS6 and APCDD1. Based on pathway analysis software, the development of acquired radioresistance in EMT6RR_MJI was hypothesized through JAK/STAT/PI3K pathway. Presently, CTLA-4 and PD-1 were determined to be associated with JAK/STAT/PI3K pathway, where both their expressions were significantly increased in EMT6RR_MJI compared to parental cells in the 1st, 4th and 8th cycle of radiation. As a conclusion, the current findings provided a mechanistic platform for the development of acquired radioresistance in EMT6RR_MJI through overexpression of CTLA-4 and PD-1, and novel knowledge on therapeutic targets for recurrent radioresistant cancers.

MeSH terms: Animals; Breast Neoplasms*; Phosphatidylinositol 3-Kinases*; Cell Line, Tumor; Mice; CTLA-4 Antigen*; Programmed Cell Death 1 Receptor*
Fulltext Four ways blue foods can help achieve food system ambitions across nations

Crona BI, Wassénius E, Jonell M, Koehn JZ, Short R, Tigchelaar M, et al.

Nature, 2023 Apr;616(7955):104-112.
PMID: 36813964 DOI: 10.1038/s41586-023-05737-x

Blue foods, sourced in aquatic environments, are important for the economies, livelihoods, nutritional security and cultures of people in many nations. They are often nutrient rich1, generate lower emissions and impacts on land and water than many terrestrial meats2, and contribute to the health3, wellbeing and livelihoods of many rural communities4. The Blue Food Assessment recently evaluated nutritional, environmental, economic and justice dimensions of blue foods globally. Here we integrate these findings and translate them into four policy objectives to help realize the contributions that blue foods can make to national food systems around the world: ensuring supplies of critical nutrients, providing healthy alternatives to terrestrial meat, reducing dietary environmental footprints and safeguarding blue food contributions to nutrition, just economies and livelihoods under a changing climate. To account for how context-specific environmental, socio-economic and cultural aspects affect this contribution, we assess the relevance of each policy objective for individual countries, and examine associated co-benefits and trade-offs at national and international scales. We find that in many African and South American nations, facilitating consumption of culturally relevant blue food, especially among nutritionally vulnerable population segments, could address vitamin B12 and omega-3 deficiencies. Meanwhile, in many global North nations, cardiovascular disease rates and large greenhouse gas footprints from ruminant meat intake could be lowered through moderate consumption of seafood with low environmental impact. The analytical framework we provide also identifies countries with high future risk, for whom climate adaptation of blue food systems will be particularly important. Overall the framework helps decision makers to assess the blue food policy objectives most relevant to their geographies, and to compare and contrast the benefits and trade-offs associated with pursuing these objectives.

MeSH terms: Cardiovascular Diseases/epidemiology; Cultural Characteristics; Diet/methods; Diet/trends; Diet/statistics & numerical data; Environment; Health Policy; Humans; Meat; Nutritional Status; Socioeconomic Factors; Fatty Acids, Omega-3; Climate Change; Carbon Footprint; Environmental Policy; Aquatic Organisms*

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