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Evidence for the Higgs Boson Decay to a Z Boson and a Photon at the LHC

Aad G, Abbott B, Abeling K, Abicht NJ, Abidi SH, Aboulhorma A, et al.

Phys Rev Lett, 2024 Jan 12;132(2):021803.
PMID: 38277607 DOI: 10.1103/PhysRevLett.132.021803

The first evidence for the Higgs boson decay to a Z boson and a photon is presented, with a statistical significance of 3.4 standard deviations. The result is derived from a combined analysis of the searches performed by the ATLAS and CMS Collaborations with proton-proton collision datasets collected at the CERN Large Hadron Collider (LHC) from 2015 to 2018. These correspond to integrated luminosities of around 140 fb^{-1} for each experiment, at a center-of-mass energy of 13 TeV. The measured signal yield is 2.2±0.7 times the standard model prediction, and agrees with the theoretical expectation within 1.9 standard deviations.
Fulltext The Relationship between Dark Triad Personality Traits and Sexting Behaviors among Adolescents and Young Adults across 11 Countries

Morelli M, Urbini F, Bianchi D, Baiocco R, Cattelino E, Laghi F, et al.

Int J Environ Res Public Health, 2021 03 04;18(5).
PMID: 33806314 DOI: 10.3390/ijerph18052526

BACKGROUND: Sexting is an increasingly common phenomenon among adolescents and young adults. Some studies have investigated the role of personality traits in different sexting behaviors within mainstream personality taxonomies like Big Five and HEXACO. However, very few studies have investigated the role of maladaptive personality factors in sexting. Therefore, the present study investigated the relationship between Dark Triad Personality Traits and experimental (i.e., sharing own sexts), risky (i.e., sexting under substance use and with strangers), and aggravated sexting (i.e., non-consensual sexting and sexting under pressure) across 11 countries.
METHODS: An online survey was completed by 6093 participants (Mage = 20.35; SDage = 3.63) from 11 different countries which covered four continents (Europe, Asia, Africa, and America). Participants completed the Sexting Behaviors Questionnaire and the 12-item Dark Triad Dirty Dozen scale.
RESULTS: Hierarchical regression analyses showed that sharing own sexts was positively predicted by Machiavellianism and Narcissism. Both risky and aggravated sexting were positively predicted by Machiavellianism and Psychopathy.
CONCLUSIONS: The present study provided empirical evidence that different sexting behaviors were predicted by Dark Triad Personality Traits, showing a relevant role of Machiavellianism in all kinds of investigated sexting behaviors. Research, clinical, and education implications for prevention programs are discussed.
Fulltext Vaginal Infections during Pregnancy Increase Breast Milk Microbiome Alpha Diversity and Alter Taxonomic Composition

Nisaa AA, Oon CE, Sreenivasan S, Balakrishnan V, Rajendran D, Tan JJ, et al.

Prev Nutr Food Sci, 2023 Mar 31;28(1):1-9.
PMID: 37066035 DOI: 10.3746/pnf.2023.28.1.1

We previously reported that breast milk from women with (W) or without (WO) vaginal yeast infection during pregnancy differs in its immunological and antimicrobial properties, especially against pathogenic vaginal Candida sp.. Here, we investigated the differences in microbiota profiles of breast milk from these groups. Seventy-two breast milk samples were collected from lactating mothers (W, n=37; WO, n=35). The DNA of bacteria was extracted from each breast milk sample for microbiota profiling by 16S rRNA gene sequencing. Breast milk from the W-group exhibited higher alpha diversity than that from the WO-group across different taxonomic levels of class (P=0.015), order (P=0.011), family (P=0.020), and genus (P=0.030). Compositional differences between groups as determined via beta diversity showed marginal differences at taxonomic levels of phylum (P=0.087), family (P=0.064), and genus (P=0.067). The W-group showed higher abundances of families Moraxellaceae (P=0.010) and Xanthomonadaceae (P=0.008), and their genera Acinetobacter (P=0.015), Enhydrobacter (P=0.015), and Stenotrophomonas (P=0.007). Meanwhile, the WO-group showed higher abundances of genus Staphylococcus (P=0.046) and species Streptococcus infantis (P=0.025). This study shows that, although breast milk composition is affected by vaginal infection during pregnancy, this may not pose a threat to infant growth and development.
Prognostic prospect of soluble programmed cell death ligand-1 in cancer management

Khairil Anwar NA, Mohd Nazri MN, Murtadha AH, Mohd Adzemi ER, Balakrishnan V, Mustaffa KMF, et al.

Acta Biochim Biophys Sin (Shanghai), 2021 Jul 28;53(8):961-978.
PMID: 34180502 DOI: 10.1093/abbs/gmab077

Aggressive tissue biopsy is commonly unavoidable in the management of most suspected tumor cases to conclusively verify the presence of cancerous cells through histological assessment. The extracted tissue is also immunostained for detection of antigens (tissue tumor markers) of potential prognostic or therapeutic importance to assist in treatment decision. Although liquid biopsies can be a powerful tool for monitoring treatment response, they are still excluded from standard cancer diagnostics, and their utility is still being debated in the scientific community. With a myriad of soluble tissue tumor markers now being discovered, liquid biopsies could completely change the current paradigms of cancer management. Recently, soluble programmed cell death ligand-1 (sPD-L1), which is found in the peripheral blood, i.e. serum and plasma, has shown potential as a pre-therapeutic predictive marker as well as a prognostic biomarker to monitor treatment efficacy. Thus, this review focuses on the emergence of sPD-L1 and promising technologies for its detection in order to support liquid biopsies for future cancer management.
Fulltext Breast milk from healthy women has higher anti-Candida properties than women with vaginal infections during pregnancy

Nisaa AA, Oon CE, Sreenivasan S, Balakrishnan V, Tan JJ, Teh CS, et al.

Food Sci Biotechnol, 2023 Mar;32(4):471-480.
PMID: 36911325 DOI: 10.1007/s10068-022-01088-x

The aim of this study was to investigate the different immunological and antimicrobial properties of breast milk from women with (W) or without (WO) vaginal yeast infections during pregnancy in 85 lactating women (W, n = 43; WO, n = 42). Concentrations of IL-10, IgA, IgM, IgG, EGF, and TGF-α were similar in both groups. However, breast milk of women aged below 31 years old from the W-group showed higher concentration of EGF than the WO-group (p = 0.031). Breast milk from WO-group exhibited higher anti-Candida properties than W-group, both via growth inhibition and aggregation of yeast cells (p
Fulltext Testing the Feasibility and Acceptability of Using an Artificial Intelligence Chatbot to Promote HIV Testing and Pre-Exposure Prophylaxis in Malaysia: Mixed Methods Study

Cheah MH, Gan YN, Altice FL, Wickersham JA, Shrestha R, Salleh NAM, et al.

JMIR Hum Factors, 2024 Jan 26;11:e52055.
PMID: 38277206 DOI: 10.2196/52055

BACKGROUND: The HIV epidemic continues to grow fastest among men who have sex with men (MSM) in Malaysia in the presence of stigma and discrimination. Engaging MSM on the internet using chatbots supported through artificial intelligence (AI) can potentially help HIV prevention efforts. We previously identified the benefits, limitations, and preferred features of HIV prevention AI chatbots and developed an AI chatbot prototype that is now tested for feasibility and acceptability.
OBJECTIVE: This study aims to test the feasibility and acceptability of an AI chatbot in promoting the uptake of HIV testing and pre-exposure prophylaxis (PrEP) in MSM.
METHODS: We conducted beta testing with 14 MSM from February to April 2022 using Zoom (Zoom Video Communications, Inc). Beta testing involved 3 steps: a 45-minute human-chatbot interaction using the think-aloud method, a 35-minute semistructured interview, and a 10-minute web-based survey. The first 2 steps were recorded, transcribed verbatim, and analyzed using the Unified Theory of Acceptance and Use of Technology. Emerging themes from the qualitative data were mapped on the 4 domains of the Unified Theory of Acceptance and Use of Technology: performance expectancy, effort expectancy, facilitating conditions, and social influence.
RESULTS: Most participants (13/14, 93%) perceived the chatbot to be useful because it provided comprehensive information on HIV testing and PrEP (performance expectancy). All participants indicated that the chatbot was easy to use because of its simple, straightforward design and quick, friendly responses (effort expectancy). Moreover, 93% (13/14) of the participants rated the overall chatbot quality as high, and all participants perceived the chatbot as a helpful tool and would refer it to others. Approximately 79% (11/14) of the participants agreed they would continue using the chatbot. They suggested adding a local language (ie, Bahasa Malaysia) to customize the chatbot to the Malaysian context (facilitating condition) and suggested that the chatbot should also incorporate more information on mental health, HIV risk assessment, and consequences of HIV. In terms of social influence, all participants perceived the chatbot as helpful in avoiding stigma-inducing interactions and thus could increase the frequency of HIV testing and PrEP uptake among MSM.
CONCLUSIONS: The current AI chatbot is feasible and acceptable to promote the uptake of HIV testing and PrEP. To ensure the successful implementation and dissemination of AI chatbots in Malaysia, they should be customized to communicate in Bahasa Malaysia and upgraded to provide other HIV-related information to improve usability, such as mental health support, risk assessment for sexually transmitted infections, AIDS treatment, and the consequences of contracting HIV.
Fulltext Triple Negative Breast Cancer: A Review of Present and Future Diagnostic Modalities

Dass SA, Tan KL, Selva Rajan R, Mokhtar NF, Mohd Adzmi ER, Wan Abdul Rahman WF, et al.

Medicina (Kaunas), 2021 Jan 12;57(1).
PMID: 33445543 DOI: 10.3390/medicina57010062

Triple-negative breast cancer (TNBC) is an aggressive breast type of cancer with no expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2). It is a highly metastasized, heterogeneous disease that accounts for 10-15% of total breast cancer cases with a poor prognosis and high relapse rate within five years after treatment compared to non-TNBC cases. The diagnostic and subtyping of TNBC tumors are essential to determine the treatment alternatives and establish personalized, targeted medications for every TNBC individual. Currently, TNBC is diagnosed via a two-step procedure of imaging and immunohistochemistry (IHC), which are operator-dependent and potentially time-consuming. Therefore, there is a crucial need for the development of rapid and advanced technologies to enhance the diagnostic efficiency of TNBC. This review discusses the overview of breast cancer with emphasis on TNBC subtypes and the current diagnostic approaches of TNBC along with its challenges. Most importantly, we have presented several promising strategies that can be utilized as future TNBC diagnostic modalities and simultaneously enhance the efficacy of TNBC diagnostic.
Fulltext A Review on Plant Cellulose Nanofibre-Based Aerogels for Biomedical Applications

Abdul Khalil HPS, Adnan AS, Yahya EB, Olaiya NG, Safrida S, Hossain MS, et al.

Polymers (Basel), 2020 Aug 06;12(8).
PMID: 32781602 DOI: 10.3390/polym12081759

Cellulose nanomaterials from plant fibre provide various potential applications (i.e., biomedical, automotive, packaging, etc.). The biomedical application of nanocellulose isolated from plant fibre, which is a carbohydrate-based source, is very viable in the 21st century. The essential characteristics of plant fibre-based nanocellulose, which include its molecular, tensile and mechanical properties, as well as its biodegradability potential, have been widely explored for functional materials in the preparation of aerogel. Plant cellulose nano fibre (CNF)-based aerogels are novel functional materials that have attracted remarkable interest. In recent years, CNF aerogel has been extensively used in the biomedical field due to its biocompatibility, renewability and biodegradability. The effective surface area of CNFs influences broad applications in biological and medical studies such as sustainable antibiotic delivery for wound healing, the preparation of scaffolds for tissue cultures, the development of drug delivery systems, biosensing and an antimicrobial film for wound healing. Many researchers have a growing interest in using CNF-based aerogels in the mentioned applications. The application of cellulose-based materials is widely reported in the literature. However, only a few studies discuss the potential of cellulose nanofibre aerogel in detail. The potential applications of CNF aerogel include composites, organic-inorganic hybrids, gels, foams, aerogels/xerogels, coatings and nano-paper, bioactive and wound dressing materials and bioconversion. The potential applications of CNF have rarely been a subject of extensive review. Thus, extensive studies to develop materials with cheaper and better properties, high prospects and effectiveness for many applications are the focus of the present work. The present review focuses on the evolution of aerogels via characterisation studies on the isolation of CNF-based aerogels. The study concludes with a description of the potential and challenges of developing sustainable materials for biomedical applications.
Fulltext Recycling Waste Cotton Cloths for the Isolation of Cellulose Nanocrystals: A Sustainable Approach

Mohamed SH, Hossain MS, Mohamad Kassim MH, Ahmad MI, Omar FM, Balakrishnan V, et al.

Polymers (Basel), 2021 Feb 19;13(4).
PMID: 33669623 DOI: 10.3390/polym13040626

There is an interest in the sustainable utilization of waste cotton cloths because of their enormous volume of generation and high cellulose content. Waste cotton cloths generated are disposed of in a landfill, which causes environmental pollution and leads to the waste of useful resources. In the present study, cellulose nanocrystals (CNCs) were isolated from waste cotton cloths collected from a landfill. The waste cotton cloths collected from the landfill were sterilized and cleaned using supercritical CO2 (scCO2) technology. The cellulose was extracted from scCO2-treated waste cotton cloths using alkaline pulping and bleaching processes. Subsequently, the CNCs were isolated using the H2SO4 hydrolysis of cellulose. The isolated CNCs were analyzed to determine the morphological, chemical, thermal, and physical properties with various analytical methods, including attenuated total reflection-Fourier transform-infrared spectroscopy (ATR-FTIR), field-emission scanning electron microscopy (FE-SEM), energy-filtered transmission electron microscopy (EF-TEM), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). The results showed that the isolated CNCs had a needle-like structure with a length and diameter of 10-30 and 2-6 nm, respectively, and an aspect ratio of 5-15, respectively. Additionally, the isolated CNCs had a high crystallinity index with a good thermal stability. The findings of the present study revealed the potential of recycling waste cotton cloths to produce a value-added product.
Fulltext Influence of Fresh Palm Fruit Sterilization in the Production of Carotenoid-Rich Virgin Palm Oil

Hassan NSM, Hossain MS, Balakrishnan V, Zuknik MH, Mustaner M, Easa AM, et al.

Foods, 2021 Nov 17;10(11).
PMID: 34829117 DOI: 10.3390/foods10112838

Palm oil is known to be rich in carotenoids and other phytonutrients. However, the carotenoids and phytonutrients degrade due to high heat sterilization of oil palm fruits. The present study was conducted to produce carotenoid-rich virgin palm oil (VPO) using cold-press extraction. Herein, the influence of sterilization of oil palm fresh fruits in the production of cold-pressed VPO was determined with varying sterilization temperatures, times, and amounts of palm fruits in sterilization. The experimental sterilization conditions were optimized using response surface methodology (RSM) based on the maximum VPO yield and minimum FFAs in cold-pressed VPO. The optimal sterilization experimental conditions of oil palm fruits were determined to be a sterilization temperature of 62 °C, a time of 90 min, and an amount of oil palm fruits of 8 kg. Under these experimental conditions, the maximum cold-pressed VPO yield and the minimal content of free fatty acids (FFAs) obtained were 27.94 wt.% and 1.32 wt.%, respectively. Several analytic methods were employed to determine cold-pressed VPO quality and fatty acids compositions and compared with the crude palm oil. It was found that cold-pressed VPO contains higher carotenoids (708 mg/g) and unsaturated fatty acids compared with the carotenoid (343 mg/g) and fatty acid compositions in CPO. The findings of the present study reveal that the sterilization temperature potentially influences the carotenoid and nutrient contents in VPO; therefore, the optimization of the sterilization conditions is crucial to producing carotenoid- and phytonutrient-rich VPO.
Fulltext Implementation of Chatbot Technology in Health Care: Protocol for a Bibliometric Analysis

Ni Z, Peng ML, Balakrishnan V, Tee V, Azwa I, Saifi R, et al.

JMIR Res Protoc, 2024 Feb 15;13:e54349.
PMID: 38228575 DOI: 10.2196/54349

BACKGROUND: Chatbots have the potential to increase people's access to quality health care. However, the implementation of chatbot technology in the health care system is unclear due to the scarce analysis of publications on the adoption of chatbot in health and medical settings.
OBJECTIVE: This paper presents a protocol of a bibliometric analysis aimed at offering the public insights into the current state and emerging trends in research related to the use of chatbot technology for promoting health.
METHODS: In this bibliometric analysis, we will select published papers from the databases of CINAHL, IEEE Xplore, PubMed, Scopus, and Web of Science that pertain to chatbot technology and its applications in health care. Our search strategy includes keywords such as "chatbot," "virtual agent," "virtual assistant," "conversational agent," "conversational AI," "interactive agent," "health," and "healthcare." Five researchers who are AI engineers and clinicians will independently review the titles and abstracts of selected papers to determine their eligibility for a full-text review. The corresponding author (ZN) will serve as a mediator to address any discrepancies and disputes among the 5 reviewers. Our analysis will encompass various publication patterns of chatbot research, including the number of annual publications, their geographic or institutional distribution, and the number of annual grants supporting chatbot research, and further summarize the methodologies used in the development of health-related chatbots, along with their features and applications in health care settings. Software tool VOSViewer (version 1.6.19; Leiden University) will be used to construct and visualize bibliometric networks.
RESULTS: The preparation for the bibliometric analysis began on December 3, 2021, when the research team started the process of familiarizing themselves with the software tools that may be used in this analysis, VOSViewer and CiteSpace, during which they consulted 3 librarians at the Yale University regarding search terms and tentative results. Tentative searches on the aforementioned databases yielded a total of 2340 papers. The official search phase started on July 27, 2023. Our goal is to complete the screening of papers and the analysis by February 15, 2024.
CONCLUSIONS: Artificial intelligence chatbots, such as ChatGPT (OpenAI Inc), have sparked numerous discussions within the health care industry regarding their impact on human health. Chatbot technology holds substantial promise for advancing health care systems worldwide. However, developing a sophisticated chatbot capable of precise interaction with health care consumers, delivering personalized care, and providing accurate health-related information and knowledge remain considerable challenges. This bibliometric analysis seeks to fill the knowledge gap in the existing literature on health-related chatbots, entailing their applications, the software used in their development, and their preferred functionalities among users.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/54349.
Optimizing supercritical carbon dioxide in the inactivation of bacteria in clinical solid waste by using response surface methodology

Hossain MS, Nik Ab Rahman NN, Balakrishnan V, Alkarkhi AF, Ahmad Rajion Z, Ab Kadir MO

Waste Manag, 2015 Apr;38:462-73.
PMID: 25636860 DOI: 10.1016/j.wasman.2015.01.003

Clinical solid waste (CSW) poses a challenge to health care facilities because of the presence of pathogenic microorganisms, leading to concerns in the effective sterilization of the CSW for safe handling and elimination of infectious disease transmission. In the present study, supercritical carbon dioxide (SC-CO2) was applied to inactivate gram-positive Staphylococcus aureus, Enterococcus faecalis, Bacillus subtilis, and gram-negative Escherichia coli in CSW. The effects of SC-CO2 sterilization parameters such as pressure, temperature, and time were investigated and optimized by response surface methodology (RSM). Results showed that the data were adequately fitted into the second-order polynomial model. The linear quadratic terms and interaction between pressure and temperature had significant effects on the inactivation of S. aureus, E. coli, E. faecalis, and B. subtilis in CSW. Optimum conditions for the complete inactivation of bacteria within the experimental range of the studied variables were 20 MPa, 60 °C, and 60 min. The SC-CO2-treated bacterial cells, observed under a scanning electron microscope, showed morphological changes, including cell breakage and dislodged cell walls, which could have caused the inactivation. This espouses the inference that SC-CO2 exerts strong inactivating effects on the bacteria present in CSW, and has the potential to be used in CSW management for the safe handling and recycling-reuse of CSW materials.
Fulltext Treatment of clinical solid waste using a steam autoclave as a possible alternative technology to incineration

Hossain MS, Balakrishnan V, Rahman NN, Sarker MZ, Kadir MO

Int J Environ Res Public Health, 2012 Mar;9(3):855-67.
PMID: 22690168 DOI: 10.3390/ijerph9030855

A steam autoclave was used to sterilize bacteria in clinical solid waste in order to determine an alternative to incineration technology in clinical solid waste management. The influence of contact time (0, 5, 15, 30 and 60 min) and temperature (111 °C, 121 °C and 131 °C) at automated saturated steam pressure was investigated. Results showed that with increasing contact time and temperature, the number of surviving bacteria decreased. The optimum experimental conditions as measured by degree of inactivation of bacteria were 121 °C for 15 minutes (min) for Gram negative bacteria, 121 °C and 131 °C for 60 and 30 min for Gram positive bacteria, respectively. The re-growth of bacteria in sterilized waste was also evaluated in the present study. It was found that bacterial re-growth started two days after the inactivation. The present study recommends that the steam autoclave cannot be considered as an alternative technology to incineration in clinical solid waste management.
Fulltext Ringed Seal Search for Global Optimization via a Sensitive Search Model

Saadi Y, Yanto IT, Herawan T, Balakrishnan V, Chiroma H, Risnumawan A

PLoS One, 2016;11(1):e0144371.
PMID: 26790131 DOI: 10.1371/journal.pone.0144371

The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global optimization problems.
Fulltext Isolation and Characterization of Magnetic Oil Palm Empty Fruits Bunch Cellulose Nanofiber Composite as a Bio-Sorbent for Cu(II) and Cr(VI) Removal

Khalid AM, Hossain MS, Ismail N, Khalil NA, Balakrishnan V, Zulkifli M, et al.

Polymers (Basel), 2020 Dec 30;13(1).
PMID: 33396583 DOI: 10.3390/polym13010112

In the present study, magnetic oil palm empty fruits bunch cellulose nanofiber (M-OPEFB-CNF) composite was isolated by sol-gel method using cellulose nanofiber (CNF) obtained from oil palm empty fruits bunch (OPEFB) and Fe3O4 as magnetite. Several analytical methods were utilized to characterize the mechanical, chemical, thermal, and morphological properties of the isolated CNF and M-OPEFB-CNF. Subsequently, the isolated M-OPEFB-CNF composite was utilized for the adsorption of Cr(VI) and Cu(II) from aqueous solution with varying parameters, such as pH, adsorbent doses, treatment time, and temperature. Results showed that the M-OPEFB-CNF as an effective bio-sorbent for the removal of Cu(II) and Cr(VI) from aqueous solution. The adsorption isotherm modeling revealed that the Freundlich equation better describes the adsorption of Cu(II) and Cr(VI) on M-OPEFB-CNF composite. The kinetics studies revealed the pseudo-second-order kinetics model was a better-described kinetics model for the removal of Cu(II) and Cr(VI) using M-OPEFB-CNF composite as bio-sorbent. The findings of the present study showed that the M-OPEFB-CNF composite has the potential to be utilized as a bio-sorbent for heavy metals removal.
Comparative transcriptomic profiling in HPV-associated cervical carcinogenesis: Implication of MHC class II and immunoglobulin heavy chain genes

Balasubramaniam SD, Wong KK, Oon CE, Balakrishnan V, Kaur G

Life Sci, 2020 Sep 01;256:118026.
PMID: 32615187 DOI: 10.1016/j.lfs.2020.118026

AIM: We aimed to determine the biological processes and pathways involved in cervical carcinogenesis associated with high-risk human papillomavirus (HPV) infection.
MATERIALS AND METHODS: Total RNA was extracted from three formalin-fixed paraffin-embedded (FFPE) samples each of normal cervix, HPV-infected low-grade squamous intraepithelial lesion (LSIL), high-grade SIL (HSIL) and squamous cell carcinoma (SCC). Transcriptomic profiling by microarrays was conducted followed by downstream Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses.
RESULTS: We examined the difference in GOs enriched for each transition stage from normal cervix to LSIL, HSIL, and SCC, and found 307 genes to be differentially expressed. In the transition from normal cervix to LSIL, the extracellular matrix (ECM) genes were significantly downregulated. The MHC class II genes were significantly upregulated in the LSIL to HSIL transition. In the final transition from HSIL to SCC, the immunoglobulin heavy locus genes were significantly upregulated and the ECM pathway was implicated.
CONCLUSION: Deregulation of the immune-related genes including MHC II and immunoglobulin heavy chain genes were involved in the transitions from LSIL to HSIL and SCC, suggesting immune escape from host anti-tumour response. The extracellular matrix plays an important role during the early and late stages of cervical carcinogenesis.
Fulltext Effect of Supporting Background Electrolytes on the Nanostructure Morphologies and Electrochemical Behaviors of Electrodeposited Gold Nanoparticles on Glassy Carbon Electrode Surfaces

Zakaria ND, Omar MH, Ahmad Kamal NN, Abdul Razak K, Sönmez T, Balakrishnan V, et al.

ACS Omega, 2021 Sep 28;6(38):24419-24431.
PMID: 34604624 DOI: 10.1021/acsomega.1c02670

Electrodeposition is an electrochemical method employed to deposit stable and robust gold nanoparticles (AuNPs) on electrode surfaces for creating chemically modified electrodes (CMEs). The use of several electrodeposition techniques with different experimental parameters allow in obtaining various surface morphologies of AuNPs deposited on the electrode surface. By considering the electrodeposition of AuNPs in various background electrolytes could play an important strategy in finding the most suitable formation of the electrodeposited AuNP films on the electrode surface. This is because different electrode roughnesses can have different effects on the electrochemical activities of the modified electrodes. Thus, in this study, the electrodeposition of AuNPs onto the glassy carbon (GC) electrode surfaces in various aqueous neutral and acidic electrolytes was achieved by using the cyclic voltammetry (CV) technique with no adjustable CV parameters. Then, surface morphologies and electrochemical activities of the electrodeposited AuNPs were investigated using scanning electron microscopy (SEM), atomic force microscopy (AFM), CV, and electrochemical impedance spectroscopy (EIS). The obtained SEM and 3D-AFM images show that AuNPs deposited at the GC electrode prepared in NaNO3 solution form a significantly better, uniform, and homogeneous electrodeposited AuNP film on the GC electrode surface with nanoparticle sizes ranging from ∼36 to 60 nm. Meanwhile, from the electrochemical performances of the AuNP-modified GC electrodes, characterized by using a mixture of ferricyanide and ferrocyanide ions [Fe(CN6)3-/4-], there is no significant difference observed in the case of charge-transfer resistances (R ct) and heterogeneous electron-transfer rate constants (k o), although there are differences in the surface morphologies of the electrodeposited AuNP films. Remarkably, the R ct values of the AuNP-modified GC electrodes are lower than those of the bare GC electrode by 18-fold, as the R ct values were found to be ∼6 Ω (p < 0.001, n = 3). This has resulted in obtaining k o values of AuNP-modified GC electrodes between the magnitude of 10-2 and 10-3 cm s-1, giving a faster electron-transfer rate than that of the bare GC electrode (10-4 cm s-1). This study confirms that using an appropriate supporting background electrolyte plays a critical role in preparing electrodeposited AuNP films. This approach could lead to nanostructures with a more densely, uniformly, and homogeneously electrodeposited AuNP film on the electrode surfaces, albeit utilizing an easy and simple preparation method.
Fulltext Minichromosome Maintenance Complex (MCM) Genes Profiling and MCM2 Protein Expression in Cervical Cancer Development

Kaur G, Balasubramaniam SD, Lee YJ, Balakrishnan V, Oon CE

Asian Pac J Cancer Prev, 2019 Oct 01;20(10):3043-3049.
PMID: 31653153 DOI: 10.31557/APJCP.2019.20.10.3043

OBJECTIVE: Minichromosome maintenance complex (MCM) proteins are essential for the process of DNA replication and cell division. This study aimed to evaluate MCM genes expression profiles and MCM2 protein in HPV-associated cervical carcinogenesis.
METHODOLOGY: MCM2, 4, 5 and 7 genes expression profiles were evaluated in three cervical tissue samples each of normal cervix, human papillomavirus (HPV)-infected low grade squamous intraepithelial lesion (LSIL), high grade squamous intraepithelial lesion (HSIL) and squamous cell carcinoma (SCC), using Human Transcriptome Array 2.0 and validated by nCounter® PanCancer Pathway NanoString Array. Immunohistochemical expression of MCM2 protein was semi-quantitatively assessed by histoscore in tissue microarrays containing 9 cases of normal cervix, 10 LSIL, 10 HSIL and 42 cases of SCC.
RESULTS: MCM2, 4, 5 and 7 genes expressions were upregulated with increasing fold change during the progression from LSIL to HSIL and the highest in SCC. MCM2 gene had the highest fold change in SCC compared to normal cervix. Immunohistochemically, MCM2 protein was localised in the nuclei of basal cells of normal cervical epithelium and dysplastic-neoplastic cells of CIN and SCC. There was a significant difference in MCM2 protein expression between the histological groups (P = 0.039), and histoscore was the highest in HSIL compared to normal cervix (P = 0.010).
CONCLUSION: The upregulation of MCM genes expressions in cervical carcinogenesis reaffirms MCM as a proliferative marker in DNA replication pathway, whereby proliferation of dysplastic and cancer cells become increasingly dysregulated and uncontrolled. A strong expression of MCM2 protein in HSIL may aid as a concatenated screening tool in detecting pre-cancerous cervical lesions.
Fulltext A deep learning approach in predicting products' sentiment ratings: a comparative analysis

Balakrishnan V, Shi Z, Law CL, Lim R, Teh LL, Fan Y

J Supercomput, 2021 Nov 05.
PMID: 34754140 DOI: 10.1007/s11227-021-04169-6

We present a benchmark comparison of several deep learning models including Convolutional Neural Networks, Recurrent Neural Network and Bi-directional Long Short Term Memory, assessed based on various word embedding approaches, including the Bi-directional Encoder Representations from Transformers (BERT) and its variants, FastText and Word2Vec. Data augmentation was administered using the Easy Data Augmentation approach resulting in two datasets (original versus augmented). All the models were assessed in two setups, namely 5-class versus 3-class (i.e., compressed version). Findings show the best prediction models were Neural Network-based using Word2Vec, with CNN-RNN-Bi-LSTM producing the highest accuracy (96%) and F-score (91.1%). Individually, RNN was the best model with an accuracy of 87.5% and F-score of 83.5%, while RoBERTa had the best F-score of 73.1%. The study shows that deep learning is better for analyzing the sentiments within the text compared to supervised machine learning and provides a direction for future work and research.
Fulltext Effectiveness of Booster Vaccinations on the Control of COVID-19 during the Spread of Omicron Variant in Malaysia

Wong MTJ, Dhaliwal SS, Balakrishnan V, Nordin F, Norazmi MN, Tye GJ

Int J Environ Res Public Health, 2023 Jan 16;20(2).
PMID: 36674401 DOI: 10.3390/ijerph20021647

(1) Background: The assessment of vaccine effectiveness against the Omicron variant is vital in the fight against COVID-19, but research on booster vaccine efficacy using nationwide data was lacking at the time of writing. This study investigates the effectiveness of booster doses on the Omicron wave in Malaysia against COVID-19 infections and deaths; (2) Methods: This study uses nationally representative data on COVID-19 from 1 January to 31 March 2022, when the Omicron variant was predominant in Malaysia. Daily new infections, deaths, ICU utilization and Rt values were compared. A screening method was used to predict the vaccine effectiveness against COVID-19 infections, whereas logistic regression was used to estimate vaccine effectiveness against COVID-19-related deaths, with efficacy comparison between AZD1222, BNT162b2 and CoronaVac; (3) Results: Malaysia's Omicron wave started at the end of January 2022, peaking on 5 March 2022. At the time of writing, statistics for daily new deaths, ICU utilization, and effective reproductive values (Rt) were showing a downtrend. Boosted vaccination is 95.4% (95% CI: 95.4, 95.4) effective in curbing COVID-19 infection, compared to non-boosted vaccination, which is 87.2% (95% CI: 87.2, 87.2). For symptomatic infection, boosted vaccination is 97.4% (95% CI: 97.4, 97.4) effective, and a non-boosted vaccination is 90.9% (95% CI: 90.9, 90.9). Against COVID-19-related death, boosted vaccination yields a vaccine effectiveness (VE) of 91.7 (95% CI: 90.6, 92.7) and full vaccination yields a VE of 65.7% (95% CI: 61.9, 69.1). Looking into the different vaccines as boosters, AZD1222 is 95.2% (CI 95%: 92.7, 96.8) effective, BNT162b2 is 91.8% (CI 95%: 90.7, 92.8) effective and CoronaVac is 88.8% (CI 95%: 84.9, 91.7) effective against COVID-19 deaths. (4) Conclusions: Boosters are effective in increasing protection against COVID-19, including the Omicron variant. Given that the VE observed was lower, CoronaVac recipients are encouraged to take boosters due to its lower VE.

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