Biodegradable ultrafiltration membrane enhanced with anti-biofouling agent from Anacardium occidentale extract.

Our research focuses on developing environmentally friendly biodegradable ultrafiltration (UF) membranes for small-scale water purification in areas lacking infrastructure or during emergencies. To address biofouling challenges without resorting to harmful chemicals, we incorporate bio-based extracts, such as methyl gallate from A. occidentale leaves, a Malaysian ulam herb, known for its quorum sensing inhibition (QSI) properties. The methyl gallate enriched extract was purified by solvent partitioning and integrated into cellulose-based UF membranes (0 to 7.5% w w-1) through phase inversion technique. The resulting membranes exhibited enhanced anti-organic fouling and anti-biofouling properties, with flux recovery ratio (FRR) of 87.84 ± 2.00% against bovine serum albumin and FRRs of 76.67 ± 1.89% and 69.57 ± 1.77% against E. coli and S. aureus, respectively. The CA/MG-5 membrane showed a 224% improvement in pure water flux (PWF) compared to the neat CA membrane. Our innovative approach significantly improves PWF, presenting an environmentally friendly method for biofouling prevention in UF membrane applications.

Fungal Spore Richness and Abundance of Allergenic Taxa: Comparing a Portable Impactor and Passive Trap Indoors and Outdoors in an Urban Setting.

Fungal spores are common airborne allergens, and fungal richness has been implicated in allergic disease. Amplicon sequencing of environmental DNA from air samples is a promising method to estimate fungal spore richness with semi-quantification of hundreds of taxa and can be combined with quantitative PCR to derive abundance estimates. However, it remains unclear how the choice of air sampling method influences these estimates. This study compared active sampling with a portable impactor and passive sampling with a passive trap over different durations to estimate fungal spore richness and the abundance of allergenic taxa. Air sampling was conducted indoors and outdoors at 12 residences, including repeated measurements with a portable impactor and passive traps with 1-day and 7-day durations. ITS2 amplicon sequence data were transformed to spore equivalents estimated by quantitative PCR, repeated active samples were combined, and abundance-based rarefaction was performed to standardize sample coverage for estimation of genus-level richness and spore abundance. Rarefied fungal richness was similar between methods indoors but higher for passive traps with a 7-day duration outdoors. Rarefied abundance of allergenic genera was similar between methods but some genera had lower abundance for passive traps with a 1-day duration, which differed indoors and outdoors indicating stochasticity in the collection of spores on collocated samplers. This study found that similar estimates of fungal spore richness and abundance of allergenic taxa can be obtained using a portable impactor or a passive trap within one day and that increased passive sample duration provides limited additional information.

Acetic acid as a protic solvent for reducing sulphuric acid concentrations in the production of cellulose nanocrystals alongside transition metal co-catalysts.

Cellulose nanocrystals (CNC) conventionally involve highly concentrated sulphuric acid, which typically resulted in the formation of undesirable by-products. Although less corrosive mineral acids have been explored as alternatives, high concentrations are still required. In this study, CNC was successfully isolated from Leucaena leucocephala wood using mild sulphuric acid with acetic acid as protic solvent, and it was further studied with the addition of Lewis acids in the form of multivalent transition metal salts as co-catalyst. Selected divalent and trivalent transition metal salts including (Cr(NO3)3, Fe(NO3)3, Co(NO3)2, and Ni(NO3)2) were investigated. The morphology, chemical structure, particle size, and physicochemical properties of the CNCs were determined. Controlled depolymerization of cellulose was observed using transmission electron microscopy (TEM). Rod-like morphology for all CNCs was obtained during the hydrolysis process with the smallest CNC particles found at an average length of 278.1 ± 35.1 nm and a diameter of 13.4 ± 3.0 nm. The results showed that higher valence state metal ions resulted in better cellulose hydrolysis efficiency. In addition, the use of transition metal salt as a co-catalyst improved production efficiency and minimised carbonization of CNC while maintaining desired crystallinity and thermal properties.

Potential role of ergothioneine rich mushroom as anti-aging candidate through elimination of neuronal senescent cells.

Oxidative stress can upset the antioxidant balance and cause accelerated aging including neurodegenerative diseases and decline in physiological function. Therefore, an antioxidant-rich diet plays a crucial role in healthy aging. This study aimed to identify and quantify mushrooms with the highest ergothioneine content through HPLC analysis and evaluate their anti-aging potential as a natural antioxidant and antisenescence in HT22 cells. Among the 14 evaluated mushroom species, Lentinula edodes (LE), shiitake mushroom contains the highest ergothioneine content and hence was used for the in-vitro studies. The cells were preincubated with ethanolic extract of ergothioneine-rich mushroom and the equimolar concentration of EGT on t-BHP-induced senescence HT22 cells. The extract was analyzed for its free radical scavenging properties using DPPH and ABTS methods. Then, the neuroprotective effect was conducted by measuring the cell viability using MTT. Senescence-associated markers and ROS staining were also analyzed. Our results revealed that a low dose of t-BHP reduces cell viability and induces senescence in HT22 cells as determined through ß-galactosidase staining and expressions of P16INK4a, P21CIPL which are the markers of cellular senescence. However, the pretreatment with ethanolic extract of LE for 8 h significantly improved the cell viability, reversed the t-BHP-induced cellular senescence in the neuronal cells, and reduced the reactive oxygen species visualized through DCFH-DA staining. These results suggest that ergothioneine-rich mushroom is a potential candidate for anti-aging exploration through the elimination of senescent cells.

Long Short-Term Memory-Based Twin Support Vector Regression for Probabilistic Load Forecasting.

A probabilistic load forecast that is accurate and reliable is crucial to not only the efficient operation of power systems but also to the efficient use of energy resources. In order to estimate the uncertainties in forecasting models and nonstationary electric load data, this study proposes a probabilistic load forecasting model, namely BFEEMD-LSTM-TWSVRSOA. This model consists of a data filtering method named fast ensemble empirical model decomposition (FEEMD) method, a twin support vector regression (TWSVR) whose features are extracted by deep learning-based long short-term memory (LSTM) networks, and parameters optimized by seeker optimization algorithms (SOAs). We compared the probabilistic forecasting performance of the BFEEMD-LSTM-TWSVRSOA and its point forecasting version with different machine learning and deep learning algorithms on Global Energy Forecasting Competition 2014 (GEFCom2014). The most representative month data of each season, totally four monthly data, collected from the one-year data in GEFCom2014, forming four datasets. Several bootstrap methods are compared in order to determine the best prediction intervals (PIs) for the proposed model. Various forecasting step sizes are also taken into consideration in order to obtain the best satisfactory point forecasting results. Experimental results on these four datasets indicate that the wild bootstrap method and 24-h step size are the best bootstrap method and forecasting step size for the proposed model. The proposed model achieves averaged 46%, 11%, 36%, and 44% better than suboptimal model on these four datasets with respect to point forecasting, and achieves averaged 53%, 48%, 46%, and 51% better than suboptimal model on these four datasets with respect to probabilistic forecasting.

Serial Casting as an Effective Method for Burn Scar Contracture Rehabilitation: A Case Series.

Guidelines and protocols for orthoses in burn scar contracture rehabilitation are limited. The current study aims to determine the optimal frequency of casting, potentially facilitating the development of a serial casting protocol. Previous literature supporting casting has low generalizability due to methodology limitations. Seven patients with burn scar contracted joints, who did not respond to traditional therapy, were recruited in this study. Patients were serially casted once, three times, or five times a week. Joint range of motion was maximized with stretching and exercise techniques before every new cast application. Across all patients, active range of motion increased from 65.8 ± 27.8° to 108.1 ± 23.3° with casting; or from 57.8 ± 16.2% to 96.7 ± 2.9% of normal. Similarly, scars improved from 9.5 ± 1.5 to 4.9 ± 1.4 on the Modified Vancouver Scar Scale score. This therapeutic effect was achieved within an average of 8.5 ± 3.7 d and 4.0 ± 2.2 new cast applications. Given the study findings, the procedures outlined could be used to develop a standardized serial casting protocol for burn scar contracture rehabilitation.

The effect of lung recruitment maneuverer in COVID-19 induced acute respiratory distress syndrome.

Coronavirus disease-2019 (COVID-19) is a highly spread infectious disease around the world. This infectious disease impacts whole body systems, specifically on respiratory system. This 57-year-old women had diagnosed COVID-19 positive and progress to acute respiratory distress syndrome (ARDS) within 1 week. Mechanical ventilation with protective lung strategy, prone position could not reverse the worsen hypoxemia and bilateral lung infiltration. Recruitment manoeuvre was proceeded with 40-40 strategy and protective/ventilation tool (P/V tool). After 4 days (8 rounds) of recruitment manoeuvre, oxygenation level and lung compliance showed dramatic improvement. The patient was finally extubated at COVID-19 Day 40 and discharged with long term oxygen use at COVID-19 Day 60. In this case, we report how recruitment manoeuvre can improve severe hypoxemia and bilateral lung infiltration dramatically in ARDS.

WAKE-mediated modulation of cVA perception via a hierarchical neuro-endocrine axis in Drosophila male-male courtship behaviour.

The nervous and endocrine systems coordinate with each other to closely influence physiological and behavioural responses in animals. Here we show that WAKE (encoded by wide awake, also known as wake) modulates membrane levels of GABAA receptor Resistance to Dieldrin (Rdl), in insulin-producing cells of adult male Drosophila melanogaster. This results in changes to secretion of insulin-like peptides which is associated with changes in juvenile hormone biosynthesis in the corpus allatum, which in turn leads to a decrease in 20-hydroxyecdysone levels. A reduction in ecdysone signalling changes neural architecture and lowers the perception of the male-specific sex pheromone 11-cis-vaccenyl acetate by odorant receptor 67d olfactory neurons. These finding explain why WAKE-deficient in Drosophila elicits significant male-male courtship behaviour.

Surveillance of Rice Blast Resistance Effectiveness and Emerging Virulent Isolates in Taiwan.

Rice blast caused by Magnaporthe oryzae is a dangerous threat to rice production and food security worldwide. Breeding and proper deployment of resistant varieties are effective and environmentally friendly strategies to manage this notorious disease. However, a highly dynamic and quickly evolved rice blast pathogen population in the field has made disease control with resistance germplasms more challenging. Therefore, continued monitoring of pathogen dynamics and application of effective resistance varieties are critical tasks to prolong or sustain field resistance. Here, we report a team project that involved evaluation of rice blast resistance genes and surveillance of M. oryzae field populations in Taiwan. A set of International Rice Research Institute-bred blast-resistant lines (IRBLs) carrying single blast resistance genes was utilized to monitor the field effectiveness of rice blast resistance. Resistance genes such as Ptr (formerly Pita2) and Pi9 exhibited the best and most durable resistance against the rice blast fungus population in Taiwan. Interestingly, line IRBLb-B harboring the Pib gene with good field protection has recently shown susceptible lesions in some locations. To dissect the genotypic features of virulent isolates against the Pib resistance gene, M. oryzae isolates were collected and analyzed. Screening of the AvrPib locus revealed that the majority of field isolates still maintained the wild-type AvrPib status but eight virulent genotypes were found. Pot3 insertion appeared to be a major way to disrupt the AvrPib avirulence function. Interestingly, a novel AvrPib double-allele genotype among virulent isolates was first identified. Pot2 repetitive element-based polymerase chain reaction (rep-PCR) fingerprinting analysis indicated that mutation events may occur independently among different lineages in different geographic locations of Taiwan. This study provides our surveillance experience of rice blast disease and serves as the foundation to sustain rice production.

A Comprehensive Review of the Technological Solutions to Analyse the Effects of Pandemic Outbreak on Human Lives.

A coronavirus outbreak caused by a novel virus known as SARS-CoV-2 originated towards the latter half of 2019. COVID-19's abrupt emergence and unchecked global expansion highlight the inability of the current healthcare services to respond to public health emergencies promptly. This paper reviews the different aspects of human life comprehensively affected by COVID-19. It then discusses various tools and technologies from the leading domains and their integration into people's lives to overcome issues resulting from pandemics. This paper further focuses on providing a detailed review of existing and probable Artificial Intelligence (AI), Internet of Things (IoT), Augmented Reality (AR), Virtual Reality (VR), and Blockchain-based solutions. The COVID-19 pandemic brings several challenges from the viewpoint of the nation's healthcare, security, privacy, and economy. AI offers different predictive services and intelligent strategies for detecting coronavirus signs, promoting drug development, remote healthcare, classifying fake news detection, and security attacks. The incorporation of AI in the COVID-19 outbreak brings robust and reliable solutions to enhance the healthcare systems, increases user's life expectancy, and boosts the nation's economy. Furthermore, AR/VR helps in distance learning, factory automation, and setting up an environment of work from home. Blockchain helps in protecting consumer's privacy, and securing the medical supply chain operations. IoT is helpful in remote patient monitoring, distant sanitising via drones, managing social distancing (using IoT cameras), and many more in combating the pandemic. This study covers an up-to-date analysis on the use of blockchain technology, AI, AR/VR, and IoT for combating COVID-19 pandemic considering various applications. These technologies provide new emerging initiatives and use cases to deal with the COVID-19 pandemic. Finally, we discuss challenges and potential research paths that will promote further research into future pandemic outbreaks.

The Effect of Electroencephalography Abnormalities on Cerebral Autoregulation in Sedated Ventilated Children.

Purpose: To determine the effects of non-ictal electroencephalogram (EEG) changes on cerebrovascular autoregulation (AR) using the cerebral oximetry index (COx). Materials and Methods: Mean arterial blood pressure (MAP), cerebral tissue oxygenation (CrSO2), and EEG were acquired for 96 h. From all of the EEG recordings, 30 min recording segments were extracted using the endotracheal suction events as the guide. EEG recordings were classified as EEG normal and EEG abnormal groups. Each 30 min segment was further divided into six 5 min epochs. Continuous recordings of MAP and CrSO2 by near-infrared spectroscopy (NIRS) were extracted. The COx value was defined as the concordance (R) value of the Pearson correlation between MAP and CrSO2 in a 5 min epoch. Then, an Independent-Samples Mann-Whitney U test was used to analyze the number of epochs within the 30 min segments above various R cutoff values (0.2, 0.3, and 0.4) in normal and abnormal EEG groups. A p-value < 0.05 was considered significant, and all analyses were two-tailed. Results: Among 16 sedated, mechanically ventilated children, 382 EEG recordings of 30 min segments were analyzed. The proportions of epochs in each 30 min segment above the R cutoff values were similar between the EEG normal and EEG abnormal groups (p > 0.05). The median concordance values for CSrO2 and MAP in EEG normal and EEG abnormal groups were similar (0.26 (0.17−0.35) and 0.18 (0.12−0.31); p = 0.09). Conclusions: Abnormal EEG patterns without ictal changes do not affect cerebrovascular autoregulation in sedated and mechanically ventilated children.

Fungal Spore Richness in School Classrooms is Related to Surrounding Forest in a Season-Dependent Manner.

Airborne fungal spores are important aeroallergens that are remarkably diverse in terms of taxonomic richness. Indoor fungal richness is dominated by outdoor fungi and is geographically patterned, but the influence of natural landscape is unclear. We aimed to elucidate the relationship between indoor fungal spore richness and natural landscape by examining the amount of surrounding forest cover. Passive sampling of airborne fungal spores was conducted in 24 schools in Taiwan during hot and cool seasons, and amplicon sequencing was used to study fungal spore (genus) richness targeting the internal transcribed spacer 2 (ITS2) region. In total, 693 fungal genera were identified, 12 of which were ubiquitous. Despite overall similarity of fungal spore richness between seasons, Basidiomycota and Ascomycota richness increased during the hot and cool seasons, respectively. Fungal spore richness in schools had a strong positive correlation with the amount of surrounding forest cover during the cool season, but not during the hot season. Fungal assemblages in schools were more similar during the hot season due to the increased ubiquity of Agaricomycetes genera. These observations indicate dispersal limitation at the kilometer scale during the cool season and increased long-distance dispersal during the hot season. Several allergenic fungi were commonly identified in schools, including some previously overlooked by conventional methods, which may be targeted as sensitizing agents in future investigations into atopic conditions. More generally, the relative importance of fungal spore richness in the development, chronicity, and severity of atopic conditions in children requires investigation.

QoS Improvement Using In-Network Caching Based on Clustering and Popularity Heuristics in CCN.

Content-Centric Networking (CCN) has emerged as a potential Internet architecture that supports name-based content retrieval mechanism in contrast to the current host location-oriented IP architecture. The in-network caching capability of CCN ensures higher content availability, lesser network delay, and leads to server load reduction. It was observed that caching the contents on each intermediate node does not use the network resources efficiently. Hence, efficient content caching decisions are crucial to improve the Quality-of-Service (QoS) for the end-user devices and improved network performance. Towards this, a novel content caching scheme is proposed in this paper. The proposed scheme first clusters the network nodes based on the hop count and bandwidth parameters to reduce content redundancy and caching operations. Then, the scheme takes content placement decisions using the cluster information, content popularity, and the hop count parameters, where the caching probability improves as the content traversed toward the requester. Hence, using the proposed heuristics, the popular contents are placed near the edges of the network to achieve a high cache hit ratio. Once the cache becomes full, the scheme implements Least-Frequently-Used (LFU) replacement scheme to substitute the least accessed content in the network routers. Extensive simulations are conducted and the performance of the proposed scheme is investigated under different network parameters that demonstrate the superiority of the proposed strategy w.r.t the peer competing strategies.

Inhibitory effect of Malaysian coastal plants on banana (Musa acuminata colla "Lakatan"), ginger (Zingiber officinale Roscoe) and sweet potato (Ipomoea batatas) polyphenol oxidase.

Undesired browning reaction catalyzed by polyphenol oxidase (PPO) has reduced the nutritional quality and customer acceptance of the products. The inhibitory effects of six coastal plants including Sonneratia alba, Rhizophora apiculata, Syzygium grande, Rhizophora mucronata, Hibiscus tiliaceus and Bruguiera gymnorhiza on PPO in banana, sweet potato and ginger were studied based on oxidation of pyrocatechol. Banana exhibited the highest PPO activity (141,600 U), followed by sweet potato (43,440 U) and ginger (26,880 U). Banana PPO was strongly inhibited by R. apiculata (70.87%) and sweet potato PPO was strongly inhibited by S. alba (82.00%). In general, most banana PPO was the most susceptible to inhibition with all inhibitors having inhibition higher than 60.00% at 0.5 mg/ml and ginger PPO was the least susceptible with all inhibitors showing less than 50.00% inhibition at 0.5 mg/ml. Coastal plant extracts are potentially to be developed as natural inhibitors for preventing enzymatic browning of fruits and vegetables.

Marker-Assisted Development and Evaluation of Monogenic Lines of Rice cv. Kaohsiung 145 Carrying Blast Resistance Genes.

Rice blast is a serious threat to global rice production. Large-scale and long-term cultivation of rice varieties with a single blast resistance gene usually leads to breakdown of resistance. To effectively control rice blast in Taiwan, marker-assisted backcrossing was conducted to develop monogenic lines carrying different blast resistance genes in the genetic background of an elite japonica rice cultivar, Kaohsiung 145 (KH145). Eleven International Rice Research Institute (IRRI)-bred blast-resistant lines (IRBLs) showing broad-spectrum resistance to local Pyricularia oryzae isolates were used as resistance donors. Sequencing analysis revealed that the recurrent parent, KH145, does not carry known resistance alleles at the target Pi2/9, Pik, Pita, and Ptr loci. For each IRBL × KH145 cross, we screened 21 to 370 (average of 108) plants per generation from the BC1F1 to BC3F1/BC4F1 generation. A total of 1,499 BC3F2/BC4F2 lines carrying homozygous resistance alleles were selected and self-crossed for four to six successive generations. The derived lines were also evaluated for background genotype using genotyping by sequencing, for blast resistance under artificial inoculation and natural infection conditions, and for agronomic performance in multiple field trials. In Chiayi and Taitung blast nurseries in 2018 to 2020, Pi2, Pi9, and Ptr conferred high resistance, Pi20 and Pik-h moderate resistance, and Pi1, Pi7, Pik-p, and Pik susceptibility to leaf blast; only Pi2, Pi9, and Ptr conferred effective resistance against panicle blast. The monogenic lines showed agronomic traits, yield, and grain quality similar to those of KH145, suggesting the potential of growing a mixture of lines to achieve durable resistance in the field.

Internet of Things: Evolution, Concerns and Security Challenges.

The escalated growth of the Internet of Things (IoT) has started to reform and reshape our lives. The deployment of a large number of objects adhered to the internet has unlocked the vision of the smart world around us, thereby paving a road towards automation and humongous data generation and collection. This automation and continuous explosion of personal and professional information to the digital world provides a potent ground to the adversaries to perform numerous cyber-attacks, thus making security in IoT a sizeable concern. Hence, timely detection and prevention of such threats are pre-requisites to prevent serious consequences. The survey conducted provides a brief insight into the technology with prime attention towards the various attacks and anomalies and their detection based on the intelligent intrusion detection system (IDS). The comprehensive look-over presented in this paper provides an in-depth analysis and assessment of diverse machine learning and deep learning-based network intrusion detection system (NIDS). Additionally, a case study of healthcare in IoT is presented. The study depicts the architecture, security, and privacy issues and application of learning paradigms in this sector. The research assessment is finally concluded by listing the results derived from the literature. Additionally, the paper discusses numerous research challenges to allow further rectifications in the approaches to deal with unusual complications.

Develop an efficient inoculation technique for Fusarium solani isolate "TJP-2178-10" pathogeny assessment in Phalaenopsis orchids.

BACKGROUND: Phalaenopsis is one of the important ornamental plants worldwide. It plays the most significant role in flower exportation in Taiwan. However, the yellow leaf disease caused by Fusarium spp. has reduced the orchid flower yield 10-50 % yearly. Varieties resistant to yellow leaf disease associated with Fusarium is urgently needed for orchid growers and breeders, and is the ultimate solution for the long-term goal. To achieve this, phenotyping is the first step and the most necessary information for further studies, such as resistance gene identification, quantitative trait loci identification, and genome-wide association study. RESULTS: The inoculation of Fusarium was performed in either abbreviated stem or detached leaf, and the pros and cons were compared. The former is the general method of phenotyping for estimating the tolerance to yellow leaf disease of Phalaenopsis, but it is time-consuming and spacy, and thus not suitable for the assessment of large numbers of samples. In contrast, the latter not only showed a similar trend of disease severity with time reduced to only one fourth of the former one but also less space needed. CONCLUSIONS: This solution allows a better phenotyping approach for the fast detection of yellow leaf disease associated with Fusarium in a large number of Phalaenopsis samples.

Identification of MaWRKY40 and MaDLO1 as Effective Marker Genes for Tracking the Salicylic Acid-Mediated Immune Response in Bananas.

Bananas are among the world's most important cash and staple crops but are threatened by various devastating pathogens. The phytohormone salicylic acid (SA) plays a key role in the regulation of plant immune response. Tracking the expression of SA-responsive marker genes under pathogen infection is important in pathogenesis elucidation. However, the common SA-responsive marker genes are not consistently induced in different banana cultivars or different organs. Here, we conducted transcriptome analysis for SA response of a banana cultivar, 'Pei-Chiao' (Cavendish, AAA genome), and identified three genes, MaWRKY40, MaWRKY70, and Downy Mildew Resistant 6 (DMR6)-Like Oxygenase 1 (MaDLO1) that are robustly induced upon SA treatment in both the leaves and roots. Consistent induction of these three genes by SA treatment was also detected in both the leaves and roots of bananas belonging to different genome types such as 'Tai-Chiao No. 7' (Cavendish, AAA genome), 'Pisang Awak' (ABB genome), and 'Lady Finger' (AA genome). Furthermore, the biotrophic pathogen cucumber mosaic virus elicited the expression of MaWRKY40 and MaDLO1 in infected leaves of susceptible cultivars. The hemibiotrophic fungal pathogen Fusarium oxysporum f. sp. cubense tropical race 4 (TR4) also consistently induced the expression of MaWRKY40 and MaDLO1 in the infected roots of the F. oxysporum f. sp. cubense TR4-resistant cultivar. These results indicate that MaWRKY40 and MaDLO1 can be used as reliable SA-responsive marker genes for the study of plant immunity in banana. Revealing SA-responsive marker genes provides a stepping stone for further studies in banana resistance to pathogens.

An overview on the chemistry, pharmacology and anticancer properties of tetrandrine and fangchinoline (alkaloids) from Stephania tetrandra roots.

Tetrandrine (TET) and fangchinoline (FAN) are dominant bisbenzylisoquinoline (BBIQ) alkaloids from the roots of Stephania tetrandra of the family Menispermaceae. BBIQ alkaloids comprise two benzylisoquinoline units linked by oxygen bridges. The molecular structures of TET and FAN are exactly the same, except that TET has a methoxy (-OCH3) group, while FAN has a hydroxyl (-OH) group at C7. In this overview, the current knowledge on the chemistry, pharmacology and anticancer properties of TET and FAN have been updated. The focus is on colon and breast cancer cells, because they are most susceptible to TET and FAN, respectively. Against colon cancer cells, TET inhibits cell proliferation and tumor growth by inducing apoptosis and G1 cell cycle arrest, and suppresses adhesion, migration and invasion of cells. Against breast cancer cells, FAN inhibits cell proliferation by inducing apoptosis, G1-phase cell cycle arrest and inhibits cell migration. The processes involve various molecular mechanisms and signaling pathways. Some insights on the ability of TET and FAN to reverse multi-drug resistance in cancer cells and suggestions for future research are provided.