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Genetic improvement of purslane (Portulaca oleracea L.) and its future prospects

Amirul Alam M, Juraimi AS, Rafii MY, Hamid AA, Kamal Uddin M, Alam MZ, et al.

Mol Biol Rep, 2014 Nov;41(11):7395-411.
PMID: 25085039 DOI: 10.1007/s11033-014-3628-1

Common purslane (Portulaca oleracea), also known as pigweed, fatweed, pusle, and little hogweed, is an annual succulent herb in the family Portulacaceae that is found in most corners of the globe. From the ancient ages purslane has been treated as a major weed of vegetables as well as other crops. However, worldwide researchers and nutritionists have studied this plant as a potential vegetable crop for humans as well as animals. Purslane is a nutritious vegetable with high antioxidant properties and recently has been recognized as the richest source of α-linolenic acid, essential omega-3 and 6 fatty acids, ascorbic acid, glutathione, α-tocopherol and β-carotene. The lack of vegetable sources of ω-3 fatty acids has resulted in a growing level of attention to introduce purslane as a new cultivated vegetable. In the rapid-revolutionizing worldwide atmosphere, the ability to produce improved planting material appropriate to diverse and varying rising conditions is a supreme precedence. Though various published reports on morphological, physiological, nutritional and medicinal aspects of purslane are available, research on the genetic improvement of this promising vegetable crop are scant. Now it is necessary to conduct research for the genetic improvement of this plant. Genetic improvement of purslane is also a real scientific challenge. Scientific modernization of conventional breeding with the advent of advance biotechnological and molecular approaches such as tissue culture, protoplast fusion, genetic transformation, somatic hybridization, marker-assisted selection, qualitative trait locus mapping, genomics, informatics and various statistical representation have opened up new opportunities of revising the relationship between genetic diversity, agronomic performance and response to breeding for varietal improvement. This review is an attempt to amalgamate the assorted scientific information on purslane propagation, cultivation, varietal improvement, nutrient analyses, medicinal uses and to describe prospective research especially for genetic improvement of this crop.
Fulltext Management of mango hopper, Idioscopus clypealis, using chemical insecticides and Neem oil

Adnan SM, Uddin MM, Alam MJ, Islam MS, Kashem MA, Rafii MY, et al.

ScientificWorldJournal, 2014;2014:709614.
PMID: 25140344 DOI: 10.1155/2014/709614

An experiment was conducted in Field Laboratory, Department of Entomology at Bangladesh Agricultural University, Mymensingh, during 2013 to manage the mango hopper, Idioscopus clypealis L, using three chemical insecticides, Imidacloprid (0.3%), Endosulfan (0.5%), and Cypermethrin (0.4%), and natural Neem oil (3%) with three replications of each. All the treatments were significantly effective in managing mango hopper in comparison to the control. Imidacloprid showed the highest efficacy in percentage of reduction of hopper population (92.50 ± 9.02) at 72 hours after treatment in case of 2nd spray. It also showed the highest overall percentage of reduction (88.59 ± 8.64) of hopper population and less toxicity to natural enemies including green ant, spider, and lacewing of mango hopper. In case of biopesticide, azadirachtin based Neem oil was found effective against mango hopper as 48.35, 60.15, and 56.54% reduction after 24, 72, and 168 hours of spraying, respectively, which was comparable with Cypermethrin as there was no statistically significant difference after 168 hours of spray. Natural enemies were also higher after 1st and 2nd spray in case of Neem oil.
Fulltext The Effect of Bottom Profile Dimples on the Femoral Head on Wear in Metal-on-Metal Total Hip Arthroplasty

Jamari J, Ammarullah MI, Saad APM, Syahrom A, Uddin M, van der Heide E, et al.

J Funct Biomater, 2021 Jun 06;12(2).
PMID: 34204138 DOI: 10.3390/jfb12020038

Wear and wear-induced debris is a significant factor in causing failure in implants. Reducing contact pressure by using a textured surface between the femoral head and acetabular cup is crucial to improving the implant's life. This study presented the effect of surface texturing as dimples on the wear evolution of total hip arthroplasty. It was implemented by developing finite element analysis from the prediction model without dimples and with bottom profile dimples of flat, drill, and ball types. Simulations were carried out by performing 3D physiological loading of the hip joint under normal walking conditions. A geometry update was initiated based on the patient's daily routine activities. Our results showed that the addition of dimples reduced contact pressure and wear. The bottom profile dimples of the ball type had the best ability to reduce wear relative to the other types, reducing cumulative linear wear by 24.3% and cumulative volumetric wear by 31% compared to no dimples. The findings demonstrated that surface texturing with appropriate dimple bottom geometry on a bearing surface is able to extend the lifetime of hip implants.
IoT empowered smart cybersecurity framework for intrusion detection in internet of drones

Ashraf SN, Manickam S, Zia SS, Abro AA, Obaidat M, Uddin M, et al.

Sci Rep, 2023 Oct 27;13(1):18422.
PMID: 37891186 DOI: 10.1038/s41598-023-45065-8

The emergence of drone-based innovative cyber security solutions integrated with the Internet of Things (IoT) has revolutionized navigational technologies with robust data communication services across multiple platforms. This advancement leverages machine learning and deep learning methods for future progress. In recent years, there has been a significant increase in the utilization of IoT-enabled drone data management technology. Industries ranging from industrial applications to agricultural advancements, as well as the implementation of smart cities for intelligent and efficient monitoring. However, these latest trends and drone-enabled IoT technology developments have also opened doors to malicious exploitation of existing IoT infrastructures. This raises concerns regarding the vulnerability of drone networks and security risks due to inherent design flaws and the lack of cybersecurity solutions and standards. The main objective of this study is to examine the latest privacy and security challenges impacting the network of drones (NoD). The research underscores the significance of establishing a secure and fortified drone network to mitigate interception and intrusion risks. The proposed system effectively detects cyber-attacks in drone networks by leveraging deep learning and machine learning techniques. Furthermore, the model's performance was evaluated using well-known drones' CICIDS2017, and KDDCup 99 datasets. We have tested the multiple hyperparameter parameters for optimal performance and classify data instances and maximum efficacy in the NoD framework. The model achieved exceptional efficiency and robustness in NoD, specifically while applying B-LSTM and LSTM. The system attains precision values of 89.10% and 90.16%, accuracy rates up to 91.00-91.36%, recall values of 81.13% and 90.11%, and F-measure values of 88.11% and 90.19% for the respective evaluation metrics.
Fulltext Therapeutic Potency of Nanoformulations of siRNAs and shRNAs in Animal Models of Cancers

Karim ME, Tha KK, Othman I, Borhan Uddin M, Chowdhury EH

Pharmaceutics, 2018 May 26;10(2).
PMID: 29861465 DOI: 10.3390/pharmaceutics10020065

RNA Interference (RNAi) has brought revolutionary transformations in cancer management in the past two decades. RNAi-based therapeutics including siRNA and shRNA have immense scope to silence the expression of mutant cancer genes specifically in a therapeutic context. Although tremendous progress has been made to establish catalytic RNA as a new class of biologics for cancer management, a lot of extracellular and intracellular barriers still pose a long-lasting challenge on the way to clinical approval. A series of chemically suitable, safe and effective viral and non-viral carriers have emerged to overcome physiological barriers and ensure targeted delivery of RNAi. The newly invented carriers, delivery techniques and gene editing technology made current treatment protocols stronger to fight cancer. This review has provided a platform about the chronicle of siRNA development and challenges of RNAi therapeutics for laboratory to bedside translation focusing on recent advancement in siRNA delivery vehicles with their limitations. Furthermore, an overview of several animal model studies of siRNA- or shRNA-based cancer gene therapy over the past 15 years has been presented, highlighting the roles of genes in multiple cancers, pharmacokinetic parameters and critical evaluation. The review concludes with a future direction for the development of catalytic RNA vehicles and design strategies to make RNAi-based cancer gene therapy more promising to surmount cancer gene delivery challenges.
Fulltext Integration of agronomic practices with herbicides for sustainable weed management in aerobic rice

Anwar MP, Juraimi AS, Mohamed MT, Uddin MK, Samedani B, Puteh A, et al.

ScientificWorldJournal, 2013;2013:916408.
PMID: 24223513 DOI: 10.1155/2013/916408

Till now, herbicide seems to be a cost effective tool from an agronomic view point to control weeds. But long term efficacy and sustainability issues are the driving forces behind the reconsideration of herbicide dependent weed management strategy in rice. This demands reappearance of physical and cultural management options combined with judicious herbicide application in a more comprehensive and integrated way. Keeping those in mind, some agronomic tools along with different manual weeding and herbicides combinations were evaluated for their weed control efficacy in rice under aerobic soil conditions. Combination of competitive variety, higher seeding rate, and seed priming resulted in more competitive cropping system in favor of rice, which was reflected in lower weed pressure, higher weed control efficiency, and better yield. Most of the herbicides exhibited excellent weed control efficiency. Treatments comprising only herbicides required less cost involvement but produced higher net benefit. On the contrary, treatments comprising both herbicide and manual weeding required high cost involvement and thus produced lower net benefit. Therefore, adoption of competitive rice variety, higher seed rate, and seed priming along with spraying different early-postemergence herbicides in rotation at 10 days after seeding (DAS) followed by a manual weeding at 30 DAS may be recommended from sustainability view point.
Dickson polynomial-based secure group authentication scheme for Internet of Things

Syed SA, Manickam S, Uddin M, Alsufyani H, Shorfuzzaman M, Selvarajan S, et al.

Sci Rep, 2024 Feb 28;14(1):4947.
PMID: 38418484 DOI: 10.1038/s41598-024-55044-2

Internet of Things (IoT) paves the way for the modern smart industrial applications and cities. Trusted Authority acts as a sole control in monitoring and maintaining the communications between the IoT devices and the infrastructure. The communication between the IoT devices happens from one trusted entity of an area to the other by way of generating security certificates. Establishing trust by way of generating security certificates for the IoT devices in a smart city application can be of high cost and expensive. In order to facilitate this, a secure group authentication scheme that creates trust amongst a group of IoT devices owned by several entities has been proposed. The majority of proposed authentication techniques are made for individual device authentication and are also utilized for group authentication; nevertheless, a unique solution for group authentication is the Dickson polynomial based secure group authentication scheme. The secret keys used in our proposed authentication technique are generated using the Dickson polynomial, which enables the group to authenticate without generating an excessive amount of network traffic overhead. IoT devices' group authentication has made use of the Dickson polynomial. Blockchain technology is employed to enable secure, efficient, and fast data transfer among the unique IoT devices of each group deployed at different places. Also, the proposed secure group authentication scheme developed based on Dickson polynomials is resistant to replay, man-in-the-middle, tampering, side channel and signature forgeries, impersonation, and ephemeral key secret leakage attacks. In order to accomplish this, we have implemented a hardware-based physically unclonable function. Implementation has been carried using python language and deployed and tested on Blockchain using Ethereum Goerli's Testnet framework. Performance analysis has been carried out by choosing various benchmarks and found that the proposed framework outperforms its counterparts through various metrics. Different parameters are also utilized to assess the performance of the proposed blockchain framework and shows that it has better performance in terms of computation, communication, storage and latency.
Fulltext Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques

Chowdhury MH, Shuzan MNI, Chowdhury MEH, Mahbub ZB, Uddin MM, Khandakar A, et al.

Sensors (Basel), 2020 Jun 01;20(11).
PMID: 32492902 DOI: 10.3390/s20113127

Hypertension is a potentially unsafe health ailment, which can be indicated directly from the blood pressure (BP). Hypertension always leads to other health complications. Continuous monitoring of BP is very important; however, cuff-based BP measurements are discrete and uncomfortable to the user. To address this need, a cuff-less, continuous, and noninvasive BP measurement system is proposed using the photoplethysmograph (PPG) signal and demographic features using machine learning (ML) algorithms. PPG signals were acquired from 219 subjects, which undergo preprocessing and feature extraction steps. Time, frequency, and time-frequency domain features were extracted from the PPG and their derivative signals. Feature selection techniques were used to reduce the computational complexity and to decrease the chance of over-fitting the ML algorithms. The features were then used to train and evaluate ML algorithms. The best regression models were selected for systolic BP (SBP) and diastolic BP (DBP) estimation individually. Gaussian process regression (GPR) along with the ReliefF feature selection algorithm outperforms other algorithms in estimating SBP and DBP with a root mean square error (RMSE) of 6.74 and 3.59, respectively. This ML model can be implemented in hardware systems to continuously monitor BP and avoid any critical health conditions due to sudden changes.
Role of melatonin in Alzheimer's disease: From preclinical studies to novel melatonin-based therapies

Roy J, Yin Wong K, Aquili L, Sahab Uddin M, Chin Heng B, Lim Tipoe G, et al.

Front Neuroendocrinol, 2022 Feb 12.
PMID: 35167824 DOI: 10.1016/j.yfrne.2022.100986

Melatonin and novel melatonin-based therapies such as melatonin-containing hybrid molecules, melatonin analogues, and melatonin derivatives have been investigated as potential therapeutics against Alzheimer's disease (AD) pathogenesis. In this review, we examine the developmental trends of melatonin therapies for AD from 1997 to 2021. We then highlight the neuroprotective mechanisms of melatonin therapy derived from preclinical studies. These mechanisms include the alleviation of amyloid-related burden, neurofibrillary tangle accumulation, oxidative stress, neuroinflammation, apoptosis, mitochondrial dysfunction, and impaired neuroplasticity and neurotransmission. We further illustrate the beneficial effects of melatonin on behavior in animal models of AD. Next, we discuss the clinical effects of melatonin on sleep, cognition, behavior, psychiatric symptoms, electroencephalography findings, and molecular biomarkers in patients with mild cognitive impairment and AD. We then explore the effectiveness of novel melatonin-based therapies. Lastly, we discuss the limitations of current melatonin therapies for AD and suggest two emerging research themes for future study.
In vivo anxiolytic and in vitro anti-inflammatory activities of water-soluble extract (WSE) of Nigella sativa (L.) seeds

Babar ZM, Jaswir I, Tareq AM, Ali Reza ASM, Azizi WM, Hafidz M, et al.

Nat Prod Res, 2021 Aug;35(16):2793-2798.
PMID: 31578877 DOI: 10.1080/14786419.2019.1667348

The WSE is a highly polar, gummy and mucilaginous bioactive content of the Nigella sativa (L.) seeds. This study reports the anxiolytic and anti-inflammatory effects of WSE investigated using Elevated Plus Maze (EPM) and Hole-Board Test (HBT) in adult mice and human RBCs haemolysis inhibition and protein denaturation respectively. The oral WSE treatment (100 & 200 mg/kg b.w/day) for 72 hours has exhibited slightly better anxiolytic effect (p
Fulltext The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis

Singla RK, De R, Efferth T, Mezzetti B, Sahab Uddin M, Sanusi, et al.

Phytomedicine, 2023 Jan;108:154520.
PMID: 36334386 DOI: 10.1016/j.phymed.2022.154520

BACKGROUND: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools.
METHODS: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST.
RESULTS AND CONCLUSION: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events.

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