Daffodil International University
UniversityDhaka, Bangladesh
Research output, citation impact, and the most-cited recent papers from Daffodil International University (Bangladesh). Aggregated across the NobleBlocks index of 300M+ scholarly works.
Top-cited papers from Daffodil International University
Inflammation is a natural protective mechanism that occurs when the body's tissue homeostatic mechanisms are disrupted by biotic, physical, or chemical agents. The immune response generates pro-inflammatory mediators, but excessive output, such as chronic inflammation, contributes to many persistent diseases. Some phenolic compounds work in tandem with nonsteroidal anti-inflammatory drugs (NSAIDs) to inhibit pro-inflammatory mediators' activity or gene expression, including cyclooxygenase (COX). Various phenolic compounds can also act on transcription factors, such as nuclear factor-κB (NF-κB) or nuclear factor-erythroid factor 2-related factor 2 (Nrf-2), to up-or downregulate elements within the antioxidant response pathways. Phenolic compounds can inhibit enzymes associated with the development of human diseases and have been used to treat various common human ailments, including hypertension, metabolic problems, incendiary infections, and neurodegenerative diseases. The inhibition of the angiotensin-converting enzyme (ACE) by phenolic compounds has been used to treat hypertension. The inhibition of carbohydrate hydrolyzing enzyme represents a type 2 diabetes mellitus therapy, and cholinesterase inhibition has been applied to treat Alzheimer's disease (AD). Phenolic compounds have also demonstrated anti-inflammatory properties to treat skin diseases, rheumatoid arthritis, and inflammatory bowel disease. Plant extracts and phenolic compounds exert protective effects against oxidative stress and inflammation caused by airborne particulate matter, in addition to a range of anti-inflammatory, anticancer, anti-aging, antibacterial, and antiviral activities. Dietary polyphenols have been used to prevent and treat allergy-related diseases. The chemical and biological contributions of phenolic compounds to cardiovascular disease have also been described. This review summarizes the recent progress delineating the multifunctional roles of phenolic compounds, including their anti-inflammatory properties and the molecular pathways through which they exert anti-inflammatory effects on metabolic disorders. This study also discusses current issues and potential prospects for the therapeutic application of phenolic compounds to various human diseases.
Cardiovascular diseases (CVD) are among the most common serious illnesses affecting human health. CVDs may be prevented or mitigated by early diagnosis, and this may reduce mortality rates. Identifying risk factors using machine learning models is a promising approach. We would like to propose a model that incorporates different methods to achieve effective prediction of heart disease. For our proposed model to be successful, we have used efficient Data Collection, Data Pre-processing and Data Transformation methods to create accurate information for the training model. We have used a combined dataset (Cleveland, Long Beach VA, Switzerland, Hungarian and Stat log). Suitable features are selected by using the Relief, and Least Absolute Shrinkage and Selection Operator (LASSO) techniques. New hybrid classifiers like Decision Tree Bagging Method (DTBM), Random Forest Bagging Method (RFBM), K-Nearest Neighbors Bagging Method (KNNBM), AdaBoost Boosting Method (ABBM), and Gradient Boosting Boosting Method (GBBM) are developed by integrating the traditional classifiers with bagging and boosting methods, which are used in the training process. We have also instrumented some machine learning algorithms to calculate the Accuracy (ACC), Sensitivity (SEN), Error Rate, Precision (PRE) and F1 Score (F1) of our model, along with the Negative Predictive Value (NPR), False Positive Rate (FPR), and False Negative Rate (FNR). The results are shown separately to provide comparisons. Based on the result analysis, we can conclude that our proposed model produced the highest accuracy while using RFBM and Relief feature selection methods (99.05%).
Cancer is one of the leading causes of death worldwide. Several treatments are available for cancer treatment, but many treatment methods are ineffective against multidrug-resistant cancer. Multidrug resistance (MDR) represents a major obstacle to effective therapeutic interventions against cancer. This review describes the known MDR mechanisms in cancer cells and discusses ongoing laboratory approaches and novel therapeutic strategies that aim to inhibit, circumvent, or reverse MDR development in various cancer types. In this review, we discuss both intrinsic and acquired drug resistance, in addition to highlighting hypoxia- and autophagy-mediated drug resistance mechanisms. Several factors, including individual genetic differences, such as mutations, altered epigenetics, enhanced drug efflux, cell death inhibition, and various other molecular and cellular mechanisms, are responsible for the development of resistance against anticancer agents. Drug resistance can also depend on cellular autophagic and hypoxic status. The expression of drug-resistant genes and the regulatory mechanisms that determine drug resistance are also discussed. Methods to circumvent MDR, including immunoprevention, the use of microparticles and nanomedicine might result in better strategies for fighting cancer.
Even though power conversion efficiency has already reached 25.8%, poor stability is one of the major challenges hindering the commercialization of perovskite solar cells (PSCs). Several initiatives, such as structural modification and fabrication techniques by numerous ways, have been employed by researchers around the world to achieve the desired level of stability. The goal of this review is to address the recent improvements in PSCs in terms of structural modification and fabrication procedures. Perovskite films are used to provide a broad range of stability and to lose up to 20% of their initial performance. A thorough comprehension of the effect of the fabrication process on the device's stability is considered to be crucial in order to provide the foundation for future attempts. We summarize several commonly used fabrication techniques - spin coating, doctor blade, sequential deposition, hybrid chemical vapor, and alternating layer-by-layer. The evolution of device structure from regular to inverted, HTL free, and ETL including the changes in material utilization from organic to inorganic, as well as the perovskite material are presented in a systematic manner. We also aimed to gain insight into the functioning stability of PSCs, as well as practical information on how to increase their operational longevity through sensible device fabrication and materials processing, to promote PSC commercialization at the end.
Agricultural production is under threat due to climate change in food insecure regions, especially in Asian countries. Various climate-driven extremes, i.e., drought, heat waves, erratic and intense rainfall patterns, storms, floods, and emerging insect pests have adversely affected the livelihood of the farmers. Future climatic predictions showed a significant increase in temperature, and erratic rainfall with higher intensity while variability exists in climatic patterns for climate extremes prediction. For mid-century (2040-2069), it is projected that there will be a rise of 2.8°C in maximum temperature and a 2.2°C in minimum temperature in Pakistan. To respond to the adverse effects of climate change scenarios, there is a need to optimize the climate-smart and resilient agricultural practices and technology for sustainable productivity. Therefore, a case study was carried out to quantify climate change effects on rice and wheat crops and to develop adaptation strategies for the rice-wheat cropping system during the mid-century (2040-2069) as these two crops have significant contributions to food production. For the quantification of adverse impacts of climate change in farmer fields, a multidisciplinary approach consisted of five climate models (GCMs), two crop models (DSSAT and APSIM) and an economic model [Trade-off Analysis, Minimum Data Model Approach (TOAMD)] was used in this case study. DSSAT predicted that there would be a yield reduction of 15.2% in rice and 14.1% in wheat and APSIM showed that there would be a yield reduction of 17.2% in rice and 12% in wheat. Adaptation technology, by modification in crop management like sowing time and density, nitrogen, and irrigation application have the potential to enhance the overall productivity and profitability of the rice-wheat cropping system under climate change scenarios. Moreover, this paper reviews current literature regarding adverse climate change impacts on agricultural productivity, associated main issues, challenges, and opportunities for sustainable productivity of agriculture to ensure food security in Asia. Flowing opportunities such as altering sowing time and planting density of crops, crop rotation with legumes, agroforestry, mixed livestock systems, climate resilient plants, livestock and fish breeds, farming of monogastric livestock, early warning systems and decision support systems, carbon sequestration, climate, water, energy, and soil smart technologies, and promotion of biodiversity have the potential to reduce the negative effects of climate change.
The field of nanotechnology is concerned with the creation and application of materials having a nanoscale spatial dimensioning. Having a considerable surface area to volume ratio, nanoparticles have particularly unique properties. Several chemical and physical strategies have been used to prepare zinc oxide nanoparticles (ZnO-NPs). Still, biological methods using green or natural routes in various underlying substances (e.g., plant extracts, enzymes, and microorganisms) can be more environmentally friendly and cost-effective than chemical and/or physical methods in the long run. ZnO-NPs are now being studied as antibacterial agents in nanoscale and microscale formulations. The purpose of this study is to analyze the prevalent traditional method of generating ZnO-NPs, as well as its harmful side effects, and how it might be addressed utilizing an eco-friendly green approach. The study's primary focus is on the potential biomedical applications of green synthesized ZnO-NPs. Biocompatibility and biomedical qualities have been improved in green-synthesized ZnO-NPs over their traditionally produced counterparts, making them excellent antibacterial and cancer-fighting drugs. Additionally, these ZnO-NPs are beneficial when combined with the healing processes of wounds and biosensing components to trace small portions of biomarkers linked with various disorders. It has also been discovered that ZnO-NPs can distribute and sense drugs. Green-synthesized ZnO-NPs are compared to traditionally synthesized ones in this review, which shows that they have outstanding potential as a potent biological agent, as well as related hazardous properties.
Digital world is growing very fast and become more complex in the volume (terabyte to petabyte), variety (structured and un-structured and hybrid), velocity (high speed in growth) in nature. This refers to as Big Data that is a global phenomenon. This is typically considered to be a data collection that has grown so large it can not be effectively managed or exploited using conventional data management tools: e.g., classic relational database management systems (RDBMS) or conventional search engines. To handle this problem, traditional RDBMS are complemented by specifically designed a rich set of alternative DBMS; such as - NoSQL, NewSQL and Search-based systems. This paper motivation is to provide - classification, characteristics and evaluation of NoSQL databases in Big Data Analytics. This report is intended to help users, especially to the organizations to obtain an independent understanding of the strengths and weaknesses of various NoSQL database approaches to supporting applications that process huge volumes of data.
Colorectal cancer (CRC) is the second most deadly cancer worldwide. CRC management is challenging due to late detection, high recurrence rate, and multi-drug resistance. Herbs and spices used in cooking, practised for generations, have been shown to contain CRC protective effect or even be useful as an anti-CRC adjuvant therapy when used in high doses. Herbs and spices contain many bioactive compounds and possess many beneficial health effects. The chemopreventive properties of these herbs and spices are mainly mediated by the BCL-2, K-ras, and MMP pathways, caspase activation, the extrinsic apoptotic pathway, and the regulation of ER-stress-induced apoptosis. As a safer natural alternative, these herbs and spices could be good candidates for chemopreventive or chemotherapeutic agents for CRC management because of their antiproliferative action on colorectal carcinoma cells and inhibitory activity on angiogenesis. Therefore, in this narrative review, six different spices and herbs: ginger ( Zingiber officinale Roscoe), turmeric ( Curcuma longa L.), garlic ( Allium sativum L.), fenugreek ( Trigonella foenum-graecum L.), sesame ( Sesamum indicum L.), and flaxseed ( Linum usitatissimum L.) used in daily cuisine were selected for this study and analyzed for their chemoprotective or chemotherapeutic roles in CRC management with underlying molecular mechanisms of actions. Initially, this study comprehensively discussed the molecular basis of CRC development, followed by culinary and traditional uses, current scientific research, and publications of selected herbs and spices on cancers. Lead compounds have been discussed comprehensively for each herb and spice, including anti-CRC phytoconstituents, antioxidant activities, anti-inflammatory properties, and finally, anti-CRC effects with treatment mechanisms. Future possible works have been suggested where applicable.
BACKGROUND: For more than three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has provided a framework to quantify health loss due to diseases, injuries, and associated risk factors. This paper presents GBD 2023 findings on disease and injury burden and risk-attributable health loss, offering a global audit of the state of world health to inform public health priorities. This work captures the evolving landscape of health metrics across age groups, sexes, and locations, while reflecting on the remaining post-COVID-19 challenges to achieving our collective global health ambitions. METHODS: The GBD 2023 combined analysis estimated years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 375 diseases and injuries, and risk-attributable burden associated with 88 modifiable risk factors. Of the more than 310 000 total data sources used for all GBD 2023 (about 30% of which were new to this estimation round), more than 120 000 sources were used for estimation of disease and injury burden and 59 000 for risk factor estimation, and included vital registration systems, surveys, disease registries, and published scientific literature. Data were analysed using previously established modelling approaches, such as disease modelling meta-regression version 2.1 (DisMod-MR 2.1) and comparative risk assessment methods. Diseases and injuries were categorised into four levels on the basis of the established GBD cause hierarchy, as were risk factors using the GBD risk hierarchy. Estimates stratified by age, sex, location, and year from 1990 to 2023 were focused on disease-specific time trends over the 2010-23 period and presented as counts (to three significant figures) and age-standardised rates per 100 000 person-years (to one decimal place). For each measure, 95% uncertainty intervals [UIs] were calculated with the 2·5th and 97·5th percentile ordered values from a 250-draw distribution. FINDINGS: Total numbers of global DALYs grew 6·1% (95% UI 4·0-8·1), from 2·64 billion (2·46-2·86) in 2010 to 2·80 billion (2·57-3·08) in 2023, but age-standardised DALY rates, which account for population growth and ageing, decreased by 12·6% (11·0-14·1), revealing large long-term health improvements. Non-communicable diseases (NCDs) contributed 1·45 billion (1·31-1·61) global DALYs in 2010, increasing to 1·80 billion (1·63-2·03) in 2023, alongside a concurrent 4·1% (1·9-6·3) reduction in age-standardised rates. Based on DALY counts, the leading level 3 NCDs in 2023 were ischaemic heart disease (193 million [176-209] DALYs), stroke (157 million [141-172]), and diabetes (90·2 million [75·2-107]), with the largest increases in age-standardised rates since 2010 occurring for anxiety disorders (62·8% [34·0-107·5]), depressive disorders (26·3% [11·6-42·9]), and diabetes (14·9% [7·5-25·6]). Remarkable health gains were made for communicable, maternal, neonatal, and nutritional (CMNN) diseases, with DALYs falling from 874 million (837-917) in 2010 to 681 million (642-736) in 2023, and a 25·8% (22·6-28·7) reduction in age-standardised DALY rates. During the COVID-19 pandemic, DALYs due to CMNN diseases rose but returned to pre-pandemic levels by 2023. From 2010 to 2023, decreases in age-standardised rates for CMNN diseases were led by rate decreases of 49·1% (32·7-61·0) for diarrhoeal diseases, 42·9% (38·0-48·0) for HIV/AIDS, and 42·2% (23·6-56·6) for tuberculosis. Neonatal disorders and lower respiratory infections remained the leading level 3 CMNN causes globally in 2023, although both showed notable rate decreases from 2010, declining by 16·5% (10·6-22·0) and 24·8% (7·4-36·7), respectively. Injury-related age-standardised DALY rates decreased by 15·6% (10·7-19·8) over the same period. Differences in burden due to NCDs, CMNN diseases, and injuries persisted across age, sex, time, and location. Based on our risk analysis, nearly 50% (1·27 billion [1·18-1·38]) of the roughly 2·80 billion total global DALYs in 2023 were attributable to the 88 risk factors analysed in GBD. Globally, the five level 3 risk factors contributing the highest proportion of risk-attributable DALYs were high systolic blood pressure (SBP), particulate matter pollution, high fasting plasma glucose (FPG), smoking, and low birthweight and short gestation-with high SBP accounting for 8·4% (6·9-10·0) of total DALYs. Of the three overarching level 1 GBD risk factor categories-behavioural, metabolic, and environmental and occupational-risk-attributable DALYs rose between 2010 and 2023 only for metabolic risks, increasing by 30·7% (24·8-37·3); however, age-standardised DALY rates attributable to metabolic risks decreased by 6·7% (2·0-11·0) over the same period. For all but three of the 25 leading level 3 risk factors, age-standardised rates dropped between 2010 and 2023-eg, declining by 54·4% (38·7-65·3) for unsafe sanitation, 50·5% (33·3-63·1) for unsafe water source, and 45·2% (25·6-72·0) for no access to handwashing facility, and by 44·9% (37·3-53·5) for child growth failure. The three leading level 3 risk factors for which age-standardised attributable DALY rates rose were high BMI (10·5% [0·1 to 20·9]), drug use (8·4% [2·6 to 15·3]), and high FPG (6·2% [-2·7 to 15·6]; non-significant). INTERPRETATION: Our findings underscore the complex and dynamic nature of global health challenges. Since 2010, there have been large decreases in burden due to CMNN diseases and many environmental and behavioural risk factors, juxtaposed with sizeable increases in DALYs attributable to metabolic risk factors and NCDs in growing and ageing populations. This long-observed consequence of the global epidemiological transition was only temporarily interrupted by the COVID-19 pandemic. The substantially decreasing CMNN disease burden, despite the 2008 global financial crisis and pandemic-related disruptions, is one of the greatest collective public health successes known. However, these achievements are at risk of being reversed due to major cuts to development assistance for health globally, the effects of which will hit low-income countries with high burden the hardest. Without sustained investment in evidence-based interventions and policies, progress could stall or reverse, leading to widespread human costs and geopolitical instability. Moreover, the rising NCD burden necessitates intensified efforts to mitigate exposure to leading risk factors-eg, air pollution, smoking, and metabolic risks, such as high SBP, BMI, and FPG-including policies that promote food security, healthier diets, physical activity, and equitable and expanded access to potential treatments, such as GLP-1 receptor agonists. Decisive, coordinated action is needed to address long-standing yet growing health challenges, including depressive and anxiety disorders. Yet this can be only part of the solution. Our response to the NCD syndemic-the complex interaction of multiple health risks, social determinants, and systemic challenges-will define the future landscape of global health. To ensure human wellbeing, economic stability, and social equity, global action to sustain and advance health gains must prioritise reducing disparities by addressing socioeconomic and demographic determinants, ensuring equitable health-care access, tackling malnutrition, strengthening health systems, and improving vaccination coverage. We live in times of great opportunity. FUNDING: Gates Foundation and Bloomberg Philanthropies.
Neuroinflammation, a protective response of the central nervous system (CNS), is associated with the pathogenesis of neurodegenerative diseases. The CNS is composed of neurons and glial cells consisting of microglia, oligodendrocytes, and astrocytes. Entry of any foreign pathogen activates the glial cells (astrocytes and microglia) and overactivation of these cells triggers the release of various neuroinflammatory markers (NMs), such as the tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), interleukin-1β (IL-10), nitric oxide (NO), and cyclooxygenase-2 (COX-2), among others. Various studies have shown the role of neuroinflammatory markers in the occurrence, diagnosis, and treatment of neurodegenerative diseases. These markers also trigger the formation of various other factors responsible for causing several neuronal diseases including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), multiple sclerosis (MS), ischemia, and several others. This comprehensive review aims to reveal the mechanism of neuroinflammatory markers (NMs), which could cause different neurodegenerative disorders. Important NMs may represent pathophysiologic processes leading to the generation of neurodegenerative diseases. In addition, various molecular alterations related to neurodegenerative diseases are discussed. Identifying these NMs may assist in the early diagnosis and detection of therapeutic targets for treating various neurodegenerative diseases.
Berberine (BBR), a potential bioactive agent, has remarkable health benefits. A substantial amount of research has been conducted to date to establish the anticancer potential of BBR. The present review consolidates salient information concerning the promising anticancer activity of this compound. The therapeutic efficacy of BBR has been reported in several studies regarding colon, breast, pancreatic, liver, oral, bone, cutaneous, prostate, intestine, and thyroid cancers. BBR prevents cancer cell proliferation by inducing apoptosis and controlling the cell cycle as well as autophagy. BBR also hinders tumor cell invasion and metastasis by down-regulating metastasis-related proteins. Moreover, BBR is also beneficial in the early stages of cancer development by lowering epithelial-mesenchymal transition protein expression. Despite its significance as a potentially promising drug candidate, there are currently no pure berberine preparations approved to treat specific ailments. Hence, this review highlights our current comprehensive knowledge of sources, extraction methods, pharmacokinetic, and pharmacodynamic profiles of berberine, as well as the proposed mechanisms of action associated with its anticancer potential. The information presented here will help provide a baseline for researchers, scientists, and drug developers regarding the use of berberine as a promising candidate in treating different types of cancers.
River pollution has been one of the main topics in the environmental issue of urban Dhaka, the capital city of Bangladesh. This study was conducted to find out the pollution situation of Turag river and the health problem of the surrounding residents. The results clearly determine that the water quality of Turag river may not be in a position to sustain the aquatic life and not suitable for using domestic purpose. This is indicated by the very low dissoloved oxygen (DO) levels and other measured parameters in the river. The maximum recorded values of pH, color, turbidity, biochemical oxygen demand (BOD5), hardness, total dissolved solids (TDS), chloride (Cl-), carbon-di-oxide (CO2) and chemical oxygen demand (COD) were 7.1 mg/L, 625 ptcu, 97.2, 4.65 mg/L, 1816 mg/L, 676mg/L, 5 mg/L, 15.5, and 78 mg/L, respectively. The maximum concentration of turbidity, BOD, hardness, TDS, and COD found in the Turag river is much higher than the standard permissible limit. The study also provides evidence that local communities are suffering from a variety of health problems including skin, diarrhea, dysentery, respiratory illnesses, anemia and complications in childbirth. Yellow fever, cholera, dengue, malaria and other epidemic diseases are also available in this area. Furthermore, the people are suffering by the odor pollution and respiratory problems.
The intriguing optoelectronic properties, diverse applications, and facile fabrication techniques of perovskite materials have garnered substantial research interest worldwide. Their outstanding performance in solar cell applications and excellent efficiency at the lab scale have already been proven. However, owing to their low stability, the widespread manufacturing of perovskite solar cells (PSCs) for commercialization is still far off. Several instability factors of PSCs, including the intrinsic and extrinsic instability of perovskite materials, have already been identified, and a variety of approaches have been adopted to improve the material quality, stability, and efficiency of PSCs. In this review, we have comprehensively presented the significance of band gap tuning in achieving both high-performance and high-stability PSCs in the presence of various degradation factors. By investigating the mechanisms of band gap engineering, we have highlighted its pivotal role in optimizing PSCs for improved efficiency and resilience.
Current advancements in nanotechnology and nanoscience have resulted in new nanomaterials, which may pose health and environmental risks. Furthermore, several researchers are working to optimize ecologically friendly procedures for creating metal and metal oxide nanoparticles. The primary goal is to decrease the adverse effects of synthetic processes, their accompanying chemicals, and the resulting complexes. Utilizing various biomaterials for nanoparticle preparation is a beneficial approach in green nanotechnology. Furthermore, using the biological qualities of nature through a variety of activities is an excellent way to achieve this goal. Algae, plants, bacteria, and fungus have been employed to make energy-efficient, low-cost, and nontoxic metallic nanoparticles in the last few decades. Despite the environmental advantages of using green chemistry-based biological synthesis over traditional methods as discussed in this article, there are some unresolved issues such as particle size and shape consistency, reproducibility of the synthesis process, and understanding of the mechanisms involved in producing metallic nanoparticles via biological entities. Consequently, there is a need for further research to analyze and comprehend the real biological synthesis-dependent processes. This is currently an untapped hot research topic that required more investment to properly leverage the green manufacturing of metallic nanoparticles through living entities. The review covers such green methods of synthesizing nanoparticles and their utilization in the scientific world.
The gradual shift towards cleaner and green energy sources requires the application of electric vehicles (EVs) as the mainstream transportation platform. The application of vehicle-to-grid (V2G) shows promise in optimizing the power demand, shaping the load variation, and increasing the sustainability of smart grids. However, no comprehensive paper has been compiled regarding the of operation of V2G and types, current ratings and types of EV in sells market, policies relevant to V2G and business model, and the implementation difficulties and current procedures used to cope with problems. This work better represents the current challenges and prospects in V2G implementation worldwide and highlights the research gap across the V2G domain. The research starts with the opportunities of V2G and required policies and business models adopted in recent years, followed by an overview of the V2G technology; then, the challenges associated with V2G on the power grid and vehicle batteries; and finally, their possible solutions. This investigation highlighted a few significant challenges, which involve a lack of a concrete V2G business model, lack of stakeholders and government incentives, the excessive burden on EV batteries during V2G, the deficiency of proper bidirectional battery charger units and standards and test beds, the injection of harmonics voltage and current to the power grid, and the possibility of uneconomical and unscheduled V2G practices. Recent research and international agency reports are revised to provide possible solutions to these bottlenecks and, in places, the requirements for additional research. The promise of V2G could be colossal, but the scheme first requires tremendous collaboration, funding, and technology maturation.
Colon cancer affects both men and women and is the world's second most significant cause of cancer-related mortality. Colon cancer death rates have risen worldwide due to the current food habit and lifestyle, which include a lot of meat, alcohol, and not enough physical exercise. As a result, novel, less harmful pharmacological treatments for colon cancer are needed now more than ever before. Colorectal cancer (CRC) affects a significant portion of the world's population. Chemotherapy's limits, as demonstrated by side effects and resistance in CRC patients, are now being sought after despite recent breakthroughs that have improved patient care and survival. Numerous chemical compounds present in medicinal herbs have shown anti-tumor and anti-apoptotic properties against various cancers, including CRC, in animal experiments. These chemicals, which come from several phytochemical families, activate several signaling pathways. This article discusses research on the anti-CRC benefits of many plants conducted in vitro, as well as the phytochemical components of plants that may play a role in the study. Researchers are also looking into the impact of these compounds on various pathways involved in cancer signaling. According to this review, anti-CRC compounds may be generated from medicinal plants. That's why we're looking at how natural items can help treat cancer while lowering the risk of developing it.
The strategies involved in the development of therapeutics for neurodegenerative disorders are very complex and challenging due to the existence of the blood-brain barrier (BBB), a closely spaced network of blood vessels and endothelial cells that functions to prevent the entry of unwanted substances in the brain. The emergence and advancement of nanotechnology shows favourable prospects to overcome this phenomenon. Engineered nanoparticles conjugated with drug moieties and imaging agents that have dimensions between 1 and 100 nm could potentially be used to ensure enhanced efficacy, cellular uptake, specific transport, and delivery of specific molecules to the brain, owing to their modified physico-chemical features. The conjugates of nanoparticles and medicinal plants, or their components known as nano phytomedicine, have been gaining significance lately in the development of novel neuro-therapeutics owing to their natural abundance, promising targeted delivery to the brain, and lesser potential to show adverse effects. In the present review, the promising application, and recent trends of combined nanotechnology and phytomedicine for the treatment of neurological disorders (ND) as compared to conventional therapies, have been addressed. Nanotechnology-based efforts performed in bioinformatics for early diagnosis as well as futuristic precision medicine in ND have also been discussed in the context of computational approach.
In the last two decades, considerable interest has been shown in understanding the development of the gut microbiota and its internal and external effects on the intestine, as well as the risk factors for cardiovascular diseases (CVDs) such as metabolic syndrome. The intestinal microbiota plays a pivotal role in human health and disease. Recent studies revealed that the gut microbiota can affect the host body. CVDs are a leading cause of morbidity and mortality, and patients favor death over chronic kidney disease. For the function of gut microbiota in the host, molecules have to penetrate the intestinal epithelium or the surface cells of the host. Gut microbiota can utilize trimethylamine, N-oxide, short-chain fatty acids, and primary and secondary bile acid pathways. By affecting these living cells, the gut microbiota can cause heart failure, atherosclerosis, hypertension, myocardial fibrosis, myocardial infarction, and coronary artery disease. Previous studies of the gut microbiota and its relation to stroke pathogenesis and its consequences can provide new therapeutic prospects. This review highlights the interplay between the microbiota and its metabolites and addresses related interventions for the treatment of CVDs.
The growth of the Internet has expanded the amount of data expressed by users across multiple platforms. The availability of these different worldviews and individuals' emotions empowers sentiment analysis. However, sentiment analysis becomes even more challenging due to a scarcity of standardized labeled data in the Bangla NLP domain. The majority of the existing Bangla research has relied on models of deep learning that significantly focus on context-independent word embeddings, such as Word2Vec, GloVe, and fastText, in which each word has a fixed representation irrespective of its context. Meanwhile, context-based pre-trained language models such as BERT have recently revolutionized the state of natural language processing. In this work, we utilized BERT's transfer learning ability to a deep integrated model CNN-BiLSTM for enhanced performance of decision-making in sentiment analysis. In addition, we also introduced the ability of transfer learning to classical machine learning algorithms for the performance comparison of CNN-BiLSTM. Additionally, we explore various word embedding techniques, such as Word2Vec, GloVe, and fastText, and compare their performance to the BERT transfer learning strategy. As a result, we have shown a state-of-the-art binary classification performance for Bangla sentiment analysis that significantly outperforms all embedding and algorithms.
Lettuce is one of the most famous leafy vegetables worldwide with lots of applications from food to other specific uses. There are different types in the lettuce group for consumers to choose from. Additionally, lettuce is an excellent source of bioactive compounds such as polyphenols, carotenoids, and chlorophyll with related health benefits. At the same time, nutrient composition and antioxidant compounds are different between lettuce varieties, especially for green and red lettuce types. The benefit of lettuce consumption depends on its composition, particularly antioxidants, which can function as nutrients. The health benefits rely on their biochemical effect when reaching the bloodstream. Some components can be released from the food matrix and altered in the digestive system. Indeed, the bioaccessibility of lettuce is measuring the quantity of these compounds released from the food matrix during digestion, which is important for health-promoting features. Extraction of bioactive compounds is one of the new trends observed in lettuce and is necessarily used for several application fields. Therefore, this review aims to demonstrate the nutritional value of lettuce and its pharmacological properties. Due to their bioaccessibility and bioavailability, the consumer will be able to comprehensively understand choosing a healthier lettuce diet. The common utilization pattern of lettuce extracted nutrients will also be summarized for further direction.