Displaying publications 1 - 20 of 33 in total

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  1. Jahan D, Al Hasan MM, Haque M
    J Pharm Bioallied Sci, 2020 04 10;12(2):163-170.
    PMID: 32742115 DOI: 10.4103/jpbs.JPBS_234_19
    Introduction: Diamond-Blackfan anemia (DBA), one of a rare group of inherited bone marrow failure syndromes, is characterized by red cell failure, the presence of congenital anomalies, and cancer predisposition. It can be caused by mutations in the RPS19 gene (25% of the cases).

    Methods: This case report describes a 10-month-old boy who presented with 2 months' history of gradually increasing weakness and pallor.

    Results: The patient was diagnosed as a case of DBA based on peripheral blood finding, bone marrow aspiration with trephine biopsy reports, and genetic mutation analysis of the RPS19 gene. His father refused hematopoietic stem cell transplantation for financial constraints. Patient received prednisolone therapy with oral folic acid and iron supplements.

    Conclusion: Hemoglobin raised from 6.7 to 9.8g/dL after 1 month of therapeutic intervention.

  2. Ferdowsi M, Hasan MM, Habib W
    Comput Methods Programs Biomed, 2024 Sep;254:108289.
    PMID: 38905988 DOI: 10.1016/j.cmpb.2024.108289
    BACKGROUND AND OBJECTIVE: Cardiovascular disease (CD) is a major global health concern, affecting millions with symptoms like fatigue and chest discomfort. Timely identification is crucial due to its significant contribution to global mortality. In healthcare, artificial intelligence (AI) holds promise for advancing disease risk assessment and treatment outcome prediction. However, machine learning (ML) evolution raises concerns about data privacy and biases, especially in sensitive healthcare applications. The objective is to develop and implement a responsible AI model for CD prediction that prioritize patient privacy, security, ensuring transparency, explainability, fairness, and ethical adherence in healthcare applications.

    METHODS: To predict CD while prioritizing patient privacy, our study employed data anonymization involved adding Laplace noise to sensitive features like age and gender. The anonymized dataset underwent analysis using a differential privacy (DP) framework to preserve data privacy. DP ensured confidentiality while extracting insights. Compared with Logistic Regression (LR), Gaussian Naïve Bayes (GNB), and Random Forest (RF), the methodology integrated feature selection, statistical analysis, and SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) for interpretability. This approach facilitates transparent and interpretable AI decision-making, aligning with responsible AI development principles. Overall, it combines privacy preservation, interpretability, and ethical considerations for accurate CD predictions.

    RESULTS: Our investigations from the DP framework with LR were promising, with an area under curve (AUC) of 0.848 ± 0.03, an accuracy of 0.797 ± 0.02, precision at 0.789 ± 0.02, recall at 0.797 ± 0.02, and an F1 score of 0.787 ± 0.02, with a comparable performance with the non-privacy framework. The SHAP and LIME based results support clinical findings, show a commitment to transparent and interpretable AI decision-making, and aligns with the principles of responsible AI development.

    CONCLUSIONS: Our study endorses a novel approach in predicting CD, amalgamating data anonymization, privacy-preserving methods, interpretability tools SHAP, LIME, and ethical considerations. This responsible AI framework ensures accurate predictions, privacy preservation, and user trust, underscoring the significance of comprehensive and transparent ML models in healthcare. Therefore, this research empowers the ability to forecast CD, providing a vital lifeline to millions of CD patients globally and potentially preventing numerous fatalities.

  3. Siddiquee S, Cheong BE, Taslima K, Kausar H, Hasan MM
    J Chromatogr Sci, 2012 Apr;50(4):358-67.
    PMID: 22407347 DOI: 10.1093/chromsci/bms012
    A simple, fast, repeatable and less laborious sample preparation protocol was developed and applied for the analysis of biocontrol fungus Trichoderma harzianum strain FA1132 by using gas chromatography-mass spectrometry. The match factors for sample spectra with respect to the mass spectra library of fungal volatile compounds were determined and used to study the complex hydrocarbons and other volatile compounds, which were separated by using different capillary columns with nonpolar, medium polar and high polar stationary phases. To date, more than 278 volatile compounds (with spectral match factor at least 90%) such as normal saturated hydrocarbons (C7-C30), cyclohexane, cyclopentane, fatty acids, alcohols, esters, sulfur-containing compounds, simple pyrane and benzene derivatives have been identified. Most of these compounds have not previously been reported. The method described in this paper is a more convenient research tool for the detection of volatile compounds from the cultures of T. harzianum.
  4. Hasan MM, Ahmed QU, Mat Soad SZ, Tunna TS
    Biomed Pharmacother, 2018 May;101:833-841.
    PMID: 29635892 DOI: 10.1016/j.biopha.2018.02.137
    Diabetes mellitus is a chronic disease which has high prevalence. The deficiency in insulin production or impaired insulin function is the underlying cause of this disease. Utilization of plant sources as a cure of diabetes has rich evidence in the history. Recently, the traditional medicinal plants have been investigated scientifically to understand the underlying mechanism behind antidiabetic potential. In this regard, a substantial number of in vivo and in vitro models have been introduced for investigating the bottom-line mechanism of the antidiabetic effect. A good number of methods have been reported to be used successfully to determine antidiabetic effects of plant extracts or isolated compounds. This review encompasses all the possible methods with a list of medicinal plants which may contribute to discovering a novel drug to treat diabetes more efficaciously with the minimum or no side effects.
  5. Hasan MM, Faruque MRI, Islam SS, Islam MT
    Materials (Basel), 2016 Oct 13;9(10).
    PMID: 28773951 DOI: 10.3390/ma9100830
    The aim of this paper is to introduce a compact double-negative (DNG) metamaterial that exhibits a negative refractive index (NRI) bandwidth of more than 3.6 GHz considering the frequency from 2 to 14 GHz. In this framework, two arms of the designed unit cell are split in a way that forms a Modified-Z-shape structure of the FR-4 substrate material. The finite integration technique (FIT)-based Computer Simulation Technology (CST) Microwave Studio is applied for computation, and the experimental setup for measuring the performance is performed inside two waveguide ports. Therefore, the measured data complies well with the simulated data of the unit cell at 0-degree and 90-degree rotation angles. The designed unit cell shows a negative refractive index from 3.482 to 7.096 GHz (bandwidth of 3.61 GHz), 7.876 to 10.047 GHz (bandwidth of 2.171 GHz), and 11.594 to 14 GHz (bandwidth of 2.406 GHz) in the microwave spectra. The design also exhibits almost the same wide negative refractive index bandwidth in the major region of the C-band and X-band if it is rotated 90 degrees. However, the novelty of the proposed structure lies in its effective medium ratio of more than 4, wide bandwidth, and compact size.
  6. Hasan MM, Faruque MRI, Islam MT
    Sci Rep, 2018 01 19;8(1):1240.
    PMID: 29352228 DOI: 10.1038/s41598-018-19705-3
    A compact metamaterial inspired antenna operate at LTE, Bluetooth and WiMAX frequency band is introduced in this paper. For the lower band, the design utilizes an outer square metallic strip forcing the patch to radiate as an equivalent magnetic-current loop. For the upper band, another magnetic current loop is created by adding metamaterial structure near the feed line on the patch. The metamaterial inspired antenna dimension of 42 × 32 mm2 compatible to wireless devices. Finite integration technique based CST Microwave Studio simulator has been used to design and numerical investigation as well as lumped circuit model of the metamaterial antenna is explained with proper mathematical derivation. The achieved measured dual band operation of the conventional antenna are sequentially, 0.561~0.578 GHz, 2.346~2.906 GHz, and 2.91~3.49 GHz, whereas the metamaterial inspired antenna shows dual-band operation from 0.60~0.64 GHz, 2.67~3.40 GHz and 3.61~3.67 GHz, respectively. Therefore, the metamaterial antenna is applicable for LTE and WiMAX applications. Besides, the measured metamaterial antenna gains of 0.15~3.81 dBi and 3.47~3.75 dBi, respectively for the frequency band of 2.67~3.40 GHz and 3.61~3.67 GHz.
  7. Gupta R, Hasan MM, Islam SZ, Yasmin T, Uddin J
    PLoS One, 2023;18(6):e0287342.
    PMID: 37319267 DOI: 10.1371/journal.pone.0287342
    The economic landscape of the United Kingdom has been significantly shaped by the intertwined issues of Brexit, COVID-19, and their interconnected impacts. Despite the country's robust and diverse economy, the disruptions caused by Brexit and the COVID-19 pandemic have created uncertainty and upheaval for both businesses and individuals. Recognizing the magnitude of these challenges, academic literature has directed its attention toward conducting immediate research in this crucial area. This study sets out to investigate key economic factors that have influenced various sectors of the UK economy and have broader economic implications within the context of Brexit and COVID-19. The factors under scrutiny include the unemployment rate, GDP index, earnings, and trade. To accomplish this, a range of data analysis tools and techniques were employed, including the Box-Jenkins method, neural network modeling, Google Trend analysis, and Twitter-sentiment analysis. The analysis encompassed different periods: pre-Brexit (2011-2016), Brexit (2016-2020), the COVID-19 period, and post-Brexit (2020-2021). The findings of the analysis offer intriguing insights spanning the past decade. For instance, the unemployment rate displayed a downward trend until 2020 but experienced a spike in 2021, persisting for a six-month period. Meanwhile, total earnings per week exhibited a gradual increase over time, and the GDP index demonstrated an upward trajectory until 2020 but declined during the COVID-19 period. Notably, trade experienced the most significant decline following both Brexit and the COVID-19 pandemic. Furthermore, the impact of these events exhibited variations across the UK's four regions and twelve industries. Wales and Northern Ireland emerged as the regions most affected by Brexit and COVID-19, with industries such as accommodation, construction, and wholesale trade particularly impacted in terms of earnings and employment levels. Conversely, industries such as finance, science, and health demonstrated an increased contribution to the UK's total GDP in the post-Brexit period, indicating some positive outcomes. It is worth highlighting that the impact of these economic factors was more pronounced on men than on women. Among all the variables analyzed, trade suffered the most severe consequences in the UK. By early 2021, the macroeconomic situation in the country was characterized by a simple dynamic: economic demand rebounded at a faster pace than supply, leading to shortages, bottlenecks, and inflation. The findings of this research carry significant value for the UK government and businesses, empowering them to adapt and innovate based on forecasts to navigate the challenges posed by Brexit and COVID-19. By doing so, they can promote long-term economic growth and effectively address the disruptions caused by these interrelated issues.
  8. Siddiquee S, Tan SG, Yusuf UK, Fatihah NH, Hasan MM
    Mol Biol Rep, 2012 Jan;39(1):715-22.
    PMID: 21553047 DOI: 10.1007/s11033-011-0790-6
    Trichoderma species are commercially applied as biocontrol agents against numerous plant pathogenic fungi due to their production of antifungal metabolites, competition for nutrients and space, and mycoparasitism. However, currently the identification of Trichoderma species from throughout the world based on micro-morphological descriptions is tedious and prone to error. The correct identification of Trichoderma species is important as several traits are species-specific. The Random Amplified Microsatellites (RAMS) analysis done using five primers in this study showed different degrees of the genetic similarity among 42 isolates of this genus. The genetic similarity values were found to be in the range of 12.50-85.11% based on a total of 76 bands scored in the Trichoderma isolates. Of these 76 bands, 96.05% were polymorphic, 3.95% were monomorphic and 16% were exclusive bands. Two bands (250 bp and 200 bp) produced by primer LR-5 and one band (250 bp) by primer P1A were present in all the Trichoderma isolates collected from healthy and infected oil palm plantation soils. Cluster analysis based on UPGMA of the RAMS marker data showed that T. harzianum, T. virens and T. longibrachiatum isolates were grouped into different clades and lineages. In this study we found that although T. aureoviride isolates were morphologically different when compared to T. harzianum isolates, the UPGMA cluster analysis showed that the majority isolates of T. aureoviride (seven from nine) were closely related to the isolates of T. harzianum.
  9. Ahamed E, Hasan MM, Faruque MRI, Mansor MFB, Abdullah S, Islam MT
    PLoS One, 2018;13(6):e0199150.
    PMID: 29924859 DOI: 10.1371/journal.pone.0199150
    In this paper, we introduce a new compact left-handed tunable metamaterial structure, inspired by a joint T-D shape geometry on a flexible NiAl2O4 substrate. The designed metamaterial exhibits an extra-large negative refractive index bandwidth of 6.34 GHz, with an operating frequency range from 4 to 18 GHz. We demonstrate the effects of substrate material thickness on the effective properties of metamaterial using two substrate materials: 1) flame retardant 4 and 2) flexible nickel aluminate. A finite integration technique based on the Computer Simulation Technology Microwave Studio electromagnetic simulator was used for our design, simulation, and investigation. A finite element method based on an HFSS (High Frequency Structure Simulator) electromagnetic simulator is also used to simulate results, perform verifications, and compare the measured results. The simulated resonance peaks occurred at 6.42 GHz (C-band), 9.32 GHz (X-band), and 16.90 GHz (Ku-band), while the measured resonance peaks occurred at 6.60 GHz (C-band), 9.16 GHz (X-band) and 17.28 GHz (Ku-band). The metamaterial structure exhibited biaxial tunable properties by changing the electromagnetic wave propagation in the y and z directions and the left-handed characteristics at 11.35 GHz and 13.50 GHz.
  10. Ahmed QU, Alhassan AM, Khatib A, Shah SAA, Hasan MM, Sarian MN
    Antioxidants (Basel), 2018 Oct 08;7(10).
    PMID: 30297618 DOI: 10.3390/antiox7100137
    The objective of the present study was to investigate the antiradical and xanthine oxidase inhibitory effects of Averrhoa bilimbi leaves. Hence, crude methanolic leaves extract and its resultant fractions, namely hexane, chloroform, and n-butanol were evaluated for 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging effect and xanthine oxidase inhibitory activity. The active constituents were tentatively identified through LC-QTOF-MS/MS and molecular docking approaches. The n-butanol fraction of A. bilimbi crude methanolic leaves extract displayed significant DPPH radical scavenging effect with IC50 (4.14 ± 0.21 μg/mL) (p < 0.05), as well as xanthine oxidase inhibitory activity with IC50 (64.84 ± 3.93 μg/mL) (p < 0.05). Afzelechin 3-O-alpha-l-rhamnopyranoside and cucumerin A were tentatively identified as possible metabolites that contribute to the antioxidant activity of the n-butanol fraction.
  11. Tuz-Zohura F, Shawon ARM, Hasan MM, Aeyas A, Chowdhury FI, Khandaker MU
    Ann Med Surg (Lond), 2023 Jul;85(7):3446-3460.
    PMID: 37427236 DOI: 10.1097/MS9.0000000000000839
    Computer-aided drug design by molecular docking, statistical analysis like multiple linear regression (MLR), principal component analysis (PCA), and molecular dynamics studies can emerge as an efficient approach to designing promising core scaffolds for coronavirus medication. The main protease [3-chymotrypsin-like protease (3CLpro)] of severe acute respiratory syndrome coronavirus (SARS-CoV)-1 and SARS-CoV-2 is one of the critical targets for designing and developing broad-spectrum antiviral therapeutic drugs. The main objective of this study was to investigate potential phytochemicals against SARS-CoV-1 and SARS-CoV-2 to ensure effective natural product-induced therapy. In this evaluation, we have selected 40 reported phytochemicals to design efficient core scaffolds that can act as potent inhibitors against the main proteases of SARS-CoV-2 and SARS-CoV-1. We categorized the selected phytochemicals into a more bioavailable and less bioavailable set, considering phytochemical drug likeliness properties. All the selected phytochemicals vigorously interacted with the catalytic dyads His41 and Cys145. Statistical analysis by MLR confirmed their contribution to structural features on binding affinities and PCA analysis for structural activity relationships for their structural pattern recognition to determine the core scaffold inhibitors. We confirmed that 4'-Hydroxyisolonchocarpin and BrussochalconeA were safe and exhibited excellent pharmacological properties. Because 4'-Hydroxyisolonchocarpin and BrussochalconeA are flavonoid derivatives, they exhibit the chalcone's ring. The presence of the reactive α,β-unsaturated system in the chalcone's rings showed different potential pharmacokinetics with an insignificant toxicological profile. Our comprehensive computational and statistical analysis reveals that these selected phytochemicals (4'-Hydroxyisolonchocarpin, BrussochalconeA) can be used to design potential broad antiviral inhibitors against SARS-CoV-2 and SARS-CoV-1.
  12. 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.
  13. Hasan MM, Madhavan P, Ahmad Noruddin NA, Lau WK, Ahmed QU, Arya A, et al.
    Pharm Biol, 2023 Dec;61(1):1135-1151.
    PMID: 37497554 DOI: 10.1080/13880209.2023.2230251
    CONTEXT: Arjunolic acid (AA) is a triterpenoid saponin found in Terminalia arjuna (Roxb.) Wight & Arn. (Combretaceae). It exerts cardiovascular protective effects as a phytomedicine. However, it is unclear how AA exerts the effects at the molecular level.

    OBJECTIVE: This study investigates the cardioprotective effects of arjunolic acid (AA) via MyD88-dependant TLR4 downstream signaling marker expression.

    MATERIALS AND METHODS: The MTT viability assay was used to assess the cytotoxicity of AA. LPS induced in vitro cardiovascular disease model was developed in H9C2 and C2C12 myotubes. The treatment groups were designed such as control (untreated), LPS control, positive control (LPS + pyrrolidine dithiocarbamate (PDTC)-25 µM), and treatment groups were co-treated with LPS and three concentrations of AA (50, 75, and 100 µM) for 24 h. The changes in the expression of TLR4 downstream signaling markers were evaluated through High Content Screening (HCS) and Western Blot (WB) analysis.

    RESULTS: After 24 h of co-treatment, the expression of TLR4, MyD88, MAPK, JNK, and NF-κB markers were upregulated significantly (2-6 times) in the LPS-treated groups compared to the untreated control in both HCS and WB experiments. Evidently, the HCS analysis revealed that MyD88, NF-κB, p38, and JNK were significantly downregulated in the H9C2 myotube in the AA treated groups. In HCS, the expression of NF-κB was downregulated in C2C12. Additionally, TLR4 expression was downregulated in both H9C2 and C2C12 myotubes in the WB experiment.

    DISCUSSION AND CONCLUSIONS: TLR4 marker expression in H9C2 and C2C12 myotubes was subsequently decreased by AA treatment, suggesting possible cardioprotective effects of AA.

  14. Charoenkwan P, Chiangjong W, Lee VS, Nantasenamat C, Hasan MM, Shoombuatong W
    Sci Rep, 2021 Feb 04;11(1):3017.
    PMID: 33542286 DOI: 10.1038/s41598-021-82513-9
    As anticancer peptides (ACPs) have attracted great interest for cancer treatment, several approaches based on machine learning have been proposed for ACP identification. Although existing methods have afforded high prediction accuracies, however such models are using a large number of descriptors together with complex ensemble approaches that consequently leads to low interpretability and thus poses a challenge for biologists and biochemists. Therefore, it is desirable to develop a simple, interpretable and efficient predictor for accurate ACP identification as well as providing the means for the rational design of new anticancer peptides with promising potential for clinical application. Herein, we propose a novel flexible scoring card method (FSCM) making use of propensity scores of local and global sequential information for the development of a sequence-based ACP predictor (named iACP-FSCM) for improving the prediction accuracy and model interpretability. To the best of our knowledge, iACP-FSCM represents the first sequence-based ACP predictor for rationalizing an in-depth understanding into the molecular basis for the enhancement of anticancer activities of peptides via the use of FSCM-derived propensity scores. The independent testing results showed that the iACP-FSCM provided accuracies of 0.825 and 0.910 as evaluated on the main and alternative datasets, respectively. Results from comparative benchmarking demonstrated that iACP-FSCM could outperform seven other existing ACP predictors with marked improvements of 7% and 17% for accuracy and MCC, respectively, on the main dataset. Furthermore, the iACP-FSCM (0.910) achieved very comparable results to that of the state-of-the-art ensemble model AntiCP2.0 (0.920) as evaluated on the alternative dataset. Comparative results demonstrated that iACP-FSCM was the most suitable choice for ACP identification and characterization considering its simplicity, interpretability and generalizability. It is highly anticipated that the iACP-FSCM may be a robust tool for the rapid screening and identification of promising ACPs for clinical use.
  15. Hasan MM, Rafii MY, Ismail MR, Mahmood M, Rahim HA, Alam MA, et al.
    Biotechnology, biotechnological equipment, 2015 Mar 04;29(2):237-254.
    PMID: 26019637
    The world's population is increasing very rapidly, reducing the cultivable land of rice, decreasing table water, emerging new diseases and pests, and the climate changes are major issues that must be addressed to researchers to develop sustainable crop varieties with resistance to biotic and abiotic stresses. However, recent scientific discoveries and advances particularly in genetics, genomics and crop physiology have opened up new opportunities to reduce the impact of these stresses which would have been difficult if not impossible as recently as the turn of the century. Marker assisted backcrossing (MABC) is one of the most promising approaches is the use of molecular markers to identify and select genes controlling resistance to those factors. Regarding this, MABC can contribute to develop resistant or high-yielding or quality rice varieties by incorporating a gene of interest into an elite variety which is already well adapted by the farmers. MABC is newly developed efficient tool by which using large population sizes (400 or more plants) for the backcross F1 generations, it is possible to recover the recurrent parent genotype using only two or three backcrosses. So far, many high yielding, biotic and abiotic stresses tolerance, quality and fragrance rice varieties have been developed in rice growing countries through MABC within the shortest timeframe. Nowadays, MABC is being used widely in plant breeding programmes to develop new variety/lines especially in rice. This paper reviews recent literature on some examples of variety/ line development using MABC strategy.
  16. Hasan MM, Rafii MY, Ismail MR, Mahmood M, Alam MA, Abdul Rahim H, et al.
    J Sci Food Agric, 2016 Mar 15;96(4):1297-305.
    PMID: 25892666 DOI: 10.1002/jsfa.7222
    Blast caused by the fungus Magnaporthe oryzae is a significant disease threat to rice across the world and is especially prevalent in Malaysia. An elite, early-maturing, high-yielding Malaysian rice variety, MR263, is susceptible to blast and was used as the recurrent parent in this study. To improve MR263 disease resistance, the Pongsu Seribu 1 rice variety was used as donor of the blast resistance Pi-7(t), Pi-d(t)1 and Pir2-3(t) genes and qLN2 quantitative trait locus (QTL). The objective was to introgress these blast resistance genes into the background of MR263 using marker-assisted backcrossing with both foreground and background selection.
  17. Chukwu SC, Rafii MY, Ramlee SI, Ismail SI, Hasan MM, Oladosu YA, et al.
    Mol Biol Rep, 2019 Feb;46(1):1519-1532.
    PMID: 30628024 DOI: 10.1007/s11033-019-04584-2
    Breeding for disease resistant varieties remains very effective and economical in controlling the bacterial leaf blight (BLB) of rice. Breeders have played a major role in developing resistant rice varieties against the BLB infection which has been adjudged to be a major disease causing significant yield reduction in rice. It would be difficult to select rice crops with multiple genes of resistance using the conventional approach alone. This is due to masking effect of genes including epistasis. In addition, conventional breeding takes a lot of time before a gene of interest can be introgressed. Linkage drag is also a major challenge in conventional approach. Molecular breeding involving markers has facilitated the characterization and introgression of BLB disease resistance genes. Biotechnology has brought another innovation in form of genetic engineering (transgenesis) of rice. Although, molecular breeding cannot be taken as a substitute for conventional breeding, molecular approach for combating BLB disease in rice is worthwhile given the demand for increased production of rice in a fast growing population of our society. This present article highlights the recent progress from conventional to molecular approach in breeding for BLB disease resistant rice varieties.
  18. Boiko DI, Shkodina AD, Hasan MM, Bardhan M, Kazmi SK, Chopra H, et al.
    Neurochem Res, 2022 Oct;47(10):2909-2924.
    PMID: 35689787 DOI: 10.1007/s11064-022-03646-5
    A complex pathogenesis involving several physiological systems is theorized to underline the development of depressive disorders. Depression is accompanied by circadian regulation disruption and interaction with the functioning of both central and peripheral oscillators. Many aspects of melatonin function unite these systems. The use of drugs for circadian rhythm disorders could inspire a potential treatment strategy for depression. Melatonin plays an essential role in the regulation of circadian rhythms. It exerts effect by activating two types of melatonin receptors, type 1A (MT1) and 1B (MT2). These are G-protein-coupled receptors, predominantly located in the central nervous system. MT1/MT2 agonists could be a useful treatment approach according to all three prevalent theories of the pathogenesis of depression involving either monoamines, synaptic remodeling, or immune/inflammatory events. MT1/MT2 receptors can be a potential target for novel antidepressants with impact on concentrations of neurotrophins or neurotransmitters, and reducing levels of pro-inflammatory cytokines. There is an interesting cross-talk mediated via the physical association of melatonin and serotonin receptors into functional heteromers. The antidepressive and neurogenetic effects of MT1/MT2 agonists can also be caused by the inhibition of the acid sphingomyelinase, leading to reduced ceramide, or increasing monoamine oxidase A levels in the hippocampus. Compounds targeting MT1 and MT2 receptors could have potential for new anti-depressants that may improve the quality of therapeutic interventions in treating depression and relieving symptoms. In particular, a combined effect on MT1 and/or MT2 receptors and neurotransmitter systems may be useful, since the normalization of the circadian rhythm through the melatonergic system will probably contribute to improved treatment. In this review, we discuss melatonergic receptors as a potential additional target for novel drugs for depression.
  19. Shkodina AD, Tan SC, Hasan MM, Abdelgawad M, Chopra H, Bilal M, et al.
    Ageing Res Rev, 2022 02;74:101554.
    PMID: 34973458 DOI: 10.1016/j.arr.2021.101554
    Parkinson's disease (PD) is a common motor disorder that has become increasingly prevalent in the ageing population. Recent works have suggested that circadian rhythms disruption is a common event in PD patients. Clock genes regulate the circadian rhythm of biological processes in eukaryotic organisms, but their roles in PD remain unclear. Despite this, several lines of evidence point to the possibility that clock genes may have a significant impact on the development and progression of the disease. This review aims to consolidate recent understanding of the roles of clock genes in PD. We first summarized the findings of clock gene expression and epigenetic analyses in PD patients and animal models. We also discussed the potential contributory role of clock gene variants in the development of PD and/or its symptoms. We further reviewed the mechanisms by which clock genes affect mitochondrial dynamics as well as the rhythmic synthesis and secretion of endocrine hormones, the impairment of which may contribute to the development of PD. Finally, we discussed the limitations of the currently available studies, and suggested future potential studies to deepen our understanding of the roles of clock genes in PD pathogenesis.
  20. Mehta A, Cheng Ng J, Andrew Awuah W, Huang H, Kalmanovich J, Agrawal A, et al.
    Ann Med Surg (Lond), 2022 Dec;84:104803.
    PMID: 36582867 DOI: 10.1016/j.amsu.2022.104803
    Robotic surgery has applications in many medical specialties, including urology, general surgery, and surgical oncology. In the context of a widespread resource and personnel shortage in Low- and Middle-Income Countries (LMICs), the use of robotics in surgery may help to reduce physician burnout, surgical site infections, and hospital stays. However, a lack of haptic feedback and potential socioeconomic factors such as high implementation costs and a lack of trained personnel may limit its accessibility and application. Specific improvements focused on improved financial and technical support to LMICs can help improve access and have the potential to transform the surgical experience for both surgeons and patients in LMICs. This review focuses on the evolution of robotic surgery, with an emphasis on challenges and recommendations to facilitate wider implementation and improved patient outcomes.
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