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Automated Brain Tumor Detection Using Machine Learning: A Bibliometric Review

Hossain R, Ibrahim RB, Hashim HB

World Neurosurg, 2023 Jul;175:57-68.
PMID: 37019303 DOI: 10.1016/j.wneu.2023.03.115

To develop a research overview of brain tumor classification using machine learning, we conducted a systematic review with a bibliometric analysis. Our systematic review and bibliometric analysis included 1747 studies of automated brain tumor detection using machine learning reported in the previous 5 years (2019-2023) from 679 different sources and authored by 6632 investigators. Bibliographic data were collected from the Scopus database, and a comprehensive bibliometric analysis was conducted using Biblioshiny and the R platform. The most productive and collaborative institutes, reports, journals, and countries were determined using citation analysis. In addition, various collaboration metrics were determined at the institute, country, and author level. Lotka's law was tested using the authors' performance. Analysis showed that the authors' publication trends followed Lotka's inverse square law. An annual publication analysis showed that 36.46% of the studies had been reported in 2022, with steady growth from previous years. Most of the cited authors had focused on multiclass classification and novel convolutional neural network models that are efficient for small training sets. A keyword analysis showed that "deep learning," "magnetic resonance imaging," "nuclear magnetic resonance imaging," and "glioma" appeared most often, proving that of the several brain tumor types, most studies had focused on glioma. India, China, and the United States were among the highest collaborative countries in terms of both authors and institutes. The University of Toronto and Harvard Medical School had the highest number of affiliations with 132 and 87 publications, respectively.
Anti-diarrheal activities of phytol along with its possible mechanism of action through in-vivo and in-silico models

Islam MT, Rahman MA, Saeed M, Ul-Haq Z, Alam MJ, Mondal M, et al.

Cell Mol Biol (Noisy-le-grand), 2020 Jun 25;66(4):243-249.
PMID: 32583783

Phytol (PHY), a chlorophyll-derived diterpenoid, exhibits numerous pharmacological properties, including antioxidant, antimicrobial, and anticancer activities. This study evaluates the anti-diarrheal effect of phytol (PHY) along with its possible mechanism of action through in-vivo and in-silico models. The effect of PHY was investigated on castor oil-induced diarrhea in Swiss mice by using prazosin, propranolol, loperamide, and nifedipine as standards with or without PHY. PHY at 50 mg/kg (p.o.) and all other standards exhibit significant (p < 0.05) anti-diarrheal effect in mice. The effect was prominent in the loperamide and propranolol groups. PHY co-treated with prazosin and propranolol was found to increase in latent periods along with a significant reduction in diarrheal section during the observation period than other individual or combined groups. Furthermore, molecular docking studies also suggested that PHY showed better interactions with the α- and β-adrenergic receptors, especially with α-ADR1a and β-ADR1. In the former case, PHY showed interaction with hydroxyl group of Ser192 at a distance of 2.91Å, while in the latter it showed hydrogen bond interactions with Thr170 and Lys297 with a distance of 2.65 and 2.72Å, respectively. PHY exerted significant anti-diarrheal effect in Swiss mice, possibly through blocking α- and β-adrenergic receptors.
Fulltext Pretreatment of Blumea lacera leaves ameliorate acute ulcer and oxidative stress in ethanol-induced Long-Evan rat: A combined experimental and chemico-biological interaction

Hossen MA, Reza ASMA, Ahmed AMA, Islam MK, Jahan I, Hossain R, et al.

Biomed Pharmacother, 2021 Mar;135:111211.
PMID: 33421733 DOI: 10.1016/j.biopha.2020.111211

Blumea lacera (Burm.f.) DC. is described as a valuable medicinal plant in various popular systems of medicine. The aim of the experiment reports the in vivo antiulcer activity of methanol extract of Blumea lacera (MEBLL) and in silico studies of bioactive constituents of MEBLL. In this study, fasted Long-Evans rat treated with 80 % ethanol (0.5 mL) to induce gastric ulcer, were pretreated orally with MEBLL at different doses (250 and 500 mg/kg, p.o., b.w) and omeprazole (20 mg/kg, p.o.) and distilled water were used as a reference drug and normal control respectively. In silico activity against gastric H+-K+ATPase enzyme was also studied. The findings demonstrated that the treatment with MEBLL attenuated markedly ulcer and protected the integrity of the gastric mucosa by preventing the mucosal ulceration altered biochemical parameters of gastric juice such total carbohydrate, total protein and pepsin activity. Additionally, the experimental groups significantly (p 
Therapeutic promises of ginkgolide A: A literature-based review

Sarkar C, Quispe C, Jamaddar S, Hossain R, Ray P, Mondal M, et al.

Biomed Pharmacother, 2020 Dec;132:110908.
PMID: 33254431 DOI: 10.1016/j.biopha.2020.110908

Ginkgolide A is a highly active platelet activating factor antagonist cage molecule which was isolated from the leaves of the Ginkgo biloba L. It is known for its inflammatory and immunological potentials. This review aims to sketch a current scenario on its therapeutic activities on the basis of scientific reports in the databases. A total 30 articles included in this review suggests that ginkgolide A has many important biological activities, including anti-inflammatory, anticancer, anxiolytic-like, anti-atherosclerosis and anti-atherombosis, neuro- and hepatoprotective effects. There is a lack of its toxicological (e.g. toxicity, cytotoxicity, genotoxicity and mutagenitcity) profile. In conclusion, ginkgolide A may be one of the potential therapeutic lead compounds, especially for the treatment of cardiovascular, hepatological, and neurological diseases and disorders. More studies are necessary on this hopeful therapeutic agent.
Fulltext Antibody response to the first dose of AZD1222 vaccine in COVID-19 convalescent and uninfected individuals in Bangladesh

Jamiruddin R, Haq A, Khondoker MU, Ali T, Ahmed F, Khandker SS, et al.

Expert Rev Vaccines, 2021 12;20(12):1651-1660.
PMID: 34503369 DOI: 10.1080/14760584.2021.1977630

BACKGROUND: Vaccination with the Oxford-AstraZeneca COVID-19 vaccine (AZD1222) initially started in the UK and quickly implemented around the Globe, including Bangladesh. Up to date, more than nine million doses administrated to the Bangladeshi public.
METHOD: Herein, we studied the antibody response to the first dose of AZD1222 in 86 Bangladeshi individuals using in-house ELISA kits. Study subjects were categorized into two groups, convalescent and uninfected, based on prior infection history and SARS-CoV-2 nucleocapsid-IgG profiles.
RESULTS: All the convalescent individuals presented elevated spike-1-IgG compared to 90% of uninfected ones after the first dose. Day >28 post-vaccination, the convalescent group showed six times higher antibody titer than the uninfected ones. The most elevated antibody titers for the former and later group were found at Day 14 and Days >28 post-vaccination, respectively. The spike-1-IgA titer showed a similar pattern as spike-1-IgG, although in a low-titer. In contrast, the IgM titer did not show any significant change in either group.
CONCLUSION: High antibody titer in the convalescent group, signify the importance of the first dose among the uninfected group. This study advocates the integration of antibody tests in vaccination programs in the healthcare system for maximizing benefit.