Uncovering the therapeutic potential of green pea waste in breast cancer: a multi-target approach utilizing LC-MS/MS metabolomics, molecular networking, and network pharmacology.

BACKGROUND PISUM SATIVUM: (PS) is a universal legume plant utilized for both human and animal consumption, particularly its seeds, known as green peas. The processing of PS in food industries and households produces a significant amount of waste that needs to be valorized. METHODS: In this study, the metabolite profiles of the 70% ethanolic extracts of PS wastes, namely peels (PSP) and a combination of leaves and stems (PSLS), were investigated by liquid chromatography-electrospray ionization-quadrupole time-of-flight tandem mass spectrometry (LC-ESI-QTOF-MS/MS) followed by molecular networking. RESULTS: Different classes of metabolites were identified, being flavonoids and their derivatives, along with phenolic acids, the most abundant categories. Additionally, a comprehensive network pharmacology strategy was applied to elucidate potentially active metabolites, key targets, and the pathways involved in cytotoxic activity against breast cancer. This cytotoxic activity was investigated in MCF-7 and MCF-10a cell lines. Results revealed that PSLS extract exhibited a potent cytotoxic activity with a good selectivity index (IC50 = 17.67 and selectivity index of 3.51), compared to the reference drug doxorubicin (IC50 = 2.69 µg/mL and selectivity index of 5.28). Whereas PSP extract appeared to be less potent and selective (IC50 = 32.92 µg/mL and selectivity index of 1.62). A similar performance was also observed for several polyphenolics isolated from the PSLS extract, including methyl cis p-coumarate, trans p-coumaric acid, and liquiritigenin/ 7-methyl liquiritigenin mixture. Methyl cis p-coumarate showed the most potent cytotoxic activity against MCF-7 cell line and the highest selectivity (IC50 = 1.18 µg/mL (6.91 µM) and selectivity index of 27.42). The network pharmacology study revealed that the isolated compounds could interact with several breast cancer-associated protein targets including carbonic anhydrases 1, 2, 4, 9, and 12, as well as aldo-keto reductase family 1 member B1, adenosine A3 receptor, protein tyrosine phosphatase non-receptor type 1, and estrogen receptor 2. CONCLUSION: The uncovered therapeutic potential of PSLS and its metabolite constituents pave the way for an efficient and mindful PS waste valorization, calling for further in-vitro and in-vivo research.

A generalized machine learning model for long-term coral reef monitoring in the Red Sea.

Coral reefs, despite covering less than 0.2 % of the ocean floor, harbor approximately 35 % of all known marine species, making their conservation critical. However, coral bleaching, exacerbated by climate change and phenomena such as El Niño, poses a significant threat to these ecosystems. This study focuses on the Red Sea, proposing a generalized machine learning approach to detect and monitor changes in coral reef cover over an 18-year period (2000-2018). Using Landsat 7 and 8 data, a Support Vector Machine (SVM) classifier was trained on depth-invariant indices (DII) derived from the Gulf of Aqaba and validated against ground truth data from Umluj. The classifier was then applied to Al Wajh, demonstrating its robustness across different sites and times. Results indicated a significant decline in coral cover: 11.4 % in the Gulf of Aqaba, 3.4 % in Umluj, and 13.6 % in Al Wajh. This study highlights the importance of continuous monitoring using generalized classifiers to mitigate the impacts of environmental changes on coral reefs.

Carob seeds as a source of bioactive flavonoid derivatives: isolation, network pharmacology-guided anti-cancer activity, and HPLC standardization.

INTRODUCTION:  Carob, Ceratonia siliqua L. (CS), is a legume well-known for its edible pod pulp. Its seeds are used almost exclusively as a source of the food additive E410. Although a variety of metabolites have been identified by HPLC and LC-MS analysis in CS, reports concerned with their isolation are scarce.   Methodology: In this study, two flavonoid derivatives were isolated from the methanolic extract of CS seeds, namely, quercetin-3-O-rhamnoside and 4'-p-hydroxybenzoylisorhamnetin-3,7-di-O-rhamnoside. Network pharmacology was unusually used as a guide for estimation of the biological potential of the isolated compounds. Finally, the methanolic extract of CS seeds and its ethyl acetate fraction were standardized for their 4'-p-hydroxybenzoylisorhamnetin-3,7-di-O-rhamnoside content by HPLC. RESULTS:  The identified isolates displayed the ability to interfere with the activity of several target proteins associated with renal and colon cancers. Their cytotoxic effect on renal and colorectal cancer cell lines was investigated in comparison to Doxorubicin. The selectivity of the isolated compounds was evaluated on normal human fetal fibroblast cell lines. The isolated 4'-p-hydroxybenzoylisorhamnetin-3,7-di-O-rhamnoside showed very potent cytotoxic activity against the tested cell lines with the highest selectivity. CONCLUSION:  CS seeds can be used as a source of bioactive flavonoid derivatives that can be incorporated in pharmaceutical industries.

Impact of Land use dynamics on the water yields in the Gorgan river basin.

This research investigates the future dynamics of water yield services in the Gorgan River Basin in the North of Iran by analyzing land cover changes from 1990 to 2020, using Landsat images and predicting up to 2040 with the Land Change Modeler and InVEST model under three scenarios: continuation, conservation, and mitigation. The results indicate significant shifts in agricultural land impacted water yields, which fluctuated from 324.7 million cubic meters (MCM) in 1990 to 279.7 MCM in 2010, before rising to 320.1 MCM by 2020. The study uniquely assesses the effects of land use changes on water yields, projecting a 13.6 % increase in water yield by 2040 under the continuation scenario, a 3.9 % increase under conservation, and a 1.6 % decrease under mitigation, which limits changes on steep slopes to prevent soil erosion and floods. This underscores the interplay between land use, vegetation cover, and water yield, emphasizing strategic land management for water resource preservation and effective watershed management in the GRB.

Evaluating future water availability in Texas through the lens of a data-driven approach leveraged with CMIP6 general circulation models.

Climate change is escalating the frequency and intensity of extreme precipitation events, significantly influencing the spatial and temporal distributions of water resources. This is particularly evident in Texas, a rapidly growing state with a pronounced west-east gradient in water supply. This study utilizes Coupled Model Intercomparison Project Phase 6 (CMIP6) data and data-driven methodology to improve projections of Texas's future water resources, focusing on actual evapotranspiration (AET) and water availability through enhanced Multi-Model Ensembles. The results reveal that the data-driven model significantly outperforms the CMIP5 and CMIP6 models across all skill metrics, underscoring the potential of data-driven methodologies in advancing climate science. Furthermore, the study provides an in-depth analysis of the projected changes in net water availability (NWA) and estimated water demand for different regions in Texas over the next six decades from 2015 to 2074, which reveal fluctuating patterns of water stress, with the regions (nine out of sixteen water planning regions in Texas, especially for the most populated regions) poised for heightened challenges in reconciling water demand and availability. While increasing trends are found in precipitation, AET, and NWA for the northern region of Texas based on SSP2-4.5, decreasing trends are found over the southern region for all three parameters based on SSP5-8.5. These findings underscore the importance of factoring both spatial and temporal variations in water availability and demand for effective water management strategies and the need for adaptive water management strategies for the changing water availability scenarios.

Identification of cyclooxygenase-II inhibitory saponins from fenugreek wastes: Insights from liquid chromatography-tandem mass spectrometry metabolomics, molecular networking, and molecular docking.

INTRODUCTION: This research explores sustainable applications for waste generated from fenugreek (Trigonella foenum-graecum), a plant with both nutritional and medicinal uses. The study specifically targets waste components as potential sources of nutrients and bioactive compounds. OBJECTIVES: The focus is to conduct detailed metabolic profiling of fenugreek waste, assess its anti-inflammatory properties by studying its cyclooxygenase (COX) inhibitory effect, and correlate this effect to the metabolite fingerprint. MATERIALS AND METHODS: Ethanolic extracts of fenugreek fruit pericarp and a combination of leaves and stems were subjected to untargeted metabolic profiling using liquid chromatography-mass spectrometry integrated with online database searches and molecular networking as an effective dereplication strategy. The study also scrutinized the COX inhibitory capabilities of these extracts and saponin-rich fractions prepared therefrom. Molecular docking was employed to investigate the specific interactions between the identified saponins and COX enzymes. RESULTS: The analysis led to the annotation of 81 metabolites, among which saponins were predominant. The saponin-rich fraction of the fruit pericarp extract displayed the strongest COX-II inhibitory activity in the in vitro inhibition assay (IC50 value of 81.64 ± 3.98 µg/mL). The molecular docking study supported the selectivity of the identified saponins towards COX-II. The two major identified saponins, namely, proto-yamogenin 3-O-[deoxyhexosyl (1 → 2)] [hexosyl (1 → 4)] hexoside 26-O-hexoside and trigofenoside A, were predicted to have the highest affinity to the COX-II receptor site. CONCLUSION: In the present study, we focused on the identification of COX-II inhibitory saponins in fenugreek waste through an integrated approach. The findings offer valuable insights into potential anti-inflammatory and cancer chemoprotective applications of fenugreek waste.

Design, synthesis, and biological evaluation of new pyrimidine-5-carbonitrile derivatives as novel anti-cancer, dual EGFRWT/COX-2 inhibitors with docking studies.

A novel series of pyrimidine-5-carbonitrile derivatives was designed, synthesized, then evaluated for their cytotoxic activity as novel anti-cancer with dual EGFRWT/COX-2 inhibitors. Two compounds 4e and 4f disclosed the highest activity against all NCI60 panel cell lines. They were most potent against Colo 205 (IC50 = 1.66, and 1.83 µM), Sequentially. The most potent two compounds disturbed cell cycle of Colo-205 cells by blocking the G1 phase, coupled with increased annexin-Vstained cells which indicated the increasing in percentage of apoptosis. In addition, 4e and 4f increase the concentration of caspase-3 by 10, and 8-fold compared to control, respectively. Moreover, the two candidate compounds were screened for cytotoxicity on normal epithelial colon cells; fortunately, they were found to be safe. Molecular docking study displayed that these compounds bound to the active site as EGFRWT/COX-2 inhibitors. Furthermore, 3D pharmacophore mapping disclosed many shared features between the most potent candidates 4e and 4f and the standard EGFRWT/COX-2 inhibitors; erlotinib, and celecoxib, respectively. Finally, the physicochemical parameter was calculated for the most potent novel anticancer candidates and the SwissAdme parameter showed that the newly synthesized compounds have good drug-likeness properties.

Anticholinesterase Activity of Budmunchiamine Alkaloids Revealed by Comparative Chemical Profiling of Two Albizia spp., Molecular Docking and Dynamic Studies.

Alzheimer's disease remains a global health challenge and an unmet need requiring innovative approaches to discover new drugs. The current study aimed to investigate the inhibitory activity of Albizia lucidior and Albizia procera leaves against acetylcholinesterase enzyme in vitro and explore their chemical compositions. Metabolic profiling of the bioactive plant, A. lucidior, via UHPLC/MS/MS-based Molecular Networking highlighted the richness of its ethanolic extract with budmunchiamine alkaloids, fourteen budmunchiamine alkaloids as well as four new putative ones were tentatively identified for the first time in A. lucidior. Pursuing these alkaloids in the fractions of A. lucidior extract via molecular networking revealed that alkaloids were mainly concentrated in the ethyl acetate fraction. In agreement, the alkaloid-rich fraction showed the most promising anticholinesterase activity (IC50 5.26 µg/mL) versus the ethanolic extract and ethyl acetate fraction of A. lucidior (IC50 24.89 and 6.90 µg/mL, respectively), compared to donepezil (IC50 3.90 µg/mL). Furthermore, deep in silico studies of tentatively identified alkaloids of A. lucidior were performed. Notably, normethyl budmunchiamine K revealed superior stability and receptor binding affinity compared to the two used references: donepezil and the co-crystallized inhibitor (MF2 700). This was concluded based on molecular docking, molecular dynamics simulations and molecular mechanics generalized born/solvent accessibility (MM-GBSA) calculations.

A Comprehensive Review of Natural Alternatives for Treatment of Alopecia with an Overview of Market Products.

Alopecia or hair loss is a widespread issue that has significant effects on personal well-being for both genders nationally and internationally. In addition, alopecia causes extreme emotional stress and negatively impacts the psychological health and self-esteem of cancer patients suffering from chemotherapy-induced alopecia. Unfortunately, available synthetic medications are costly, invasive, or have extreme adverse effects. On the contrary, natural and herbal hair loss products are widely available in the local and international markets in variable pharmaceutical forms with different mechanisms of action, namely, androgen antagonists, nutritional supplements, vasodilators, and 5α-reductase inhibitors or dihydrotestosterone blockers. Thus, it is of great importance to encourage researchers to investigate these natural alternatives that can act as potent therapeutic agents having diverse mechanisms of action as well as limited side effects. Currently, natural remedies are considered a fast-rising pharmaceutical segment with demand from a wide range of consumers. In this study, we present a review of reported herbal remedies and herb combinations recommended for hair loss and their mode of action, along with an overview of available market products and formulations, their composition, and declared effects. In addition, a general outline of the different forms of alopecia, its causes, and recommended treatments are mentioned as well. This was all done with the aim of assisting further studies with developing standardized natural formulations for alopecia as many were found to lack standardization of their bioactive ingredients and efficiency confirmation.

Multi-sectoral impact assessment of an extreme African dust episode in the Eastern Mediterranean in March 2018.

In late March 2018, a large part of the Eastern Mediterranean experienced an extraordinary episode of African dust, one of the most intense in recent years, here referred to as the "Minoan Red" event. The episode mainly affected the Greek island of Crete, where the highest aerosol concentrations over the past 15 yeas were recorded, although impacts were also felt well beyond this core area. Our study fills a gap in dust research by assessing the multi-sectoral impacts of sand and dust storms and their socioeconomic implications. Specifically, we provide a multi-sectoral impact assessment of Crete during the occurrence of this exceptional African dust event. During the day of the occurrence of the maximum dust concentration in Crete, i.e. March 22nd, 2018, we identified impacts on meteorological conditions, agriculture, transport, energy, society (including closing of schools and cancellation of social events), and emergency response systems. As a result, the event led to a 3-fold increase in daily emergency responses compare to previous days associated with urban emergencies and wildfires, a 3.5-fold increase in hospital visits and admissions for Chronic Obstructive Pulmonary Disease (COPD) exacerbations and dyspnoea, a reduction of visibility causing aircraft traffic disruptions (eleven cancellations and seven delays), and a reduction of solar energy production. We estimate the cost of direct and indirect effects of the dust episode, considering the most affected socio-economic sectors (e.g. civil protection, aviation, health and solar energy production), to be between 3.4 and 3.8 million EUR for Crete. Since such desert dust transport episodes are natural, meteorology-driven and thus to a large extent unavoidable, we argue that the efficiency of actions to mitigate dust impacts depends on the accuracy of operational dust forecasting and the implementation of relevant early warning systems for social awareness.

Enhanced Antioxidant, Antiviral, and Anticancer Activities of the Extract of Fermented Egyptian Rice Bran Complexed with Hydroxypropyl-ß-cyclodextrin.

Egyptian rice bran was fermented with baker's yeast, and released phenolics were extracted with aqueous methanol to give fermented rice bran extract (FRBE). The analysis of the FRBE with ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry revealed 21 compounds, mainly phenolic acids and flavonoids. The FRBE was then complexed with (2-hydroxypropyl)-ß-cyclodextrin (HPßCD) via noncovalent host-guest inclusion complexation using the thin-film hydration technique to improve the hydrophilicity and bioactivity of the FRBE. The formation of the inclusion complex was confirmed using HPLC, 1H NMR, FT-IR, and a phase solubility study. In addition, the biological activities of the complex were investigated. The FRBE/HPßCD inclusion complex had more pronounced antioxidant, antiviral, and anticancer activities compared to free FRBE. These findings warrant the future investigation of potential medical applications of FRBE.

Identification of Antibacterial Metabolites from Endophytic Fungus Aspergillus fumigatus, Isolated from Albizia lucidior Leaves (Fabaceae), Utilizing Metabolomic and Molecular Docking Techniques.

The rapid spread of bacterial infection caused by Staphylococcus aureus has become a problem to public health despite the presence of past trials devoted to controlling the infection. Thus, the current study aimed to explore the chemical composition of the extract of endophytic fungus Aspergillus fumigatus, isolated from Albizia lucidior leaves, and investigate the antimicrobial activity of isolated metabolites and their probable mode of actions. The chemical investigation of the fungal extract via UPLC/MS/MS led to the identification of at least forty-two metabolites, as well as the isolation and complete characterization of eight reported metabolites. The antibacterial activities of isolated metabolites were assessed against S. aureus using agar disc diffusion and microplate dilution methods. Compounds ergosterol, helvolic acid and monomethyl sulochrin-4-sulphate showed minimal inhibitory concentration (MIC) values of 15.63, 1.95 and 3.90 µg/mL, respectively, compared to ciprofloxacin. We also report the inhibitory activity of the fungal extract on DNA gyrase and topoisomerase IV, which led us to perform molecular docking using the three most active compounds isolated from the extract against both enzymes. These active compounds had the required structural features for S. aureus DNA gyrase and topoisomerase IV inhibition, evidenced via molecular docking.

Potential Mechanisms Involved in the Protective Effect of Dicaffeoylquinic Acids from Artemisia annua L. Leaves against Diabetes and Its Complications.

Diabetes mellitus is a chronic disease affecting the globe and its incidence is increasing pandemically. The use of plant-derived natural products for diabetes management is of great interest. Polar fraction of Artemisia annua L. leaves has shown antidiabetic activity in vivo. In the present study, three major compounds were isolated from this polar fraction; namely, 3,5-dicaffeoylquinic acid (1); 4,5-dicaffeoylquinic acid (2), and 3,4- dicaffeoylquinic acid methyl ester (3), using VLC-RP-18 and HPLC techniques. The potential protective effects of these compounds against diabetes and its complications were investigated by employing various in vitro enzyme inhibition assays. Furthermore, their antioxidant and wound healing effectiveness were evaluated. Results declared that these dicaffeoylquinic acids greatly inhibited DPPIV enzyme while moderately inhibited α-glucosidase enzyme, where compounds 1 and 3 displayed the most prominent effects. In addition, compound 3 showed pronounced inhibition of α-amylase enzyme. Moreover, these compounds markedly inhibited aldose reductase enzyme and exerted powerful antioxidant effects, among which compound 3 exhibited the highest activity implying a notable potentiality in impeding diabetes complications. Interestingly, compounds 2 and 3 moderately accelerated scratch wound healing. Our findings suggest that these dicaffeoylquinic acids can be promising therapeutic agents for managing diabetes and its complications.

The efficacy of Origanum majorana nanocubosomal systems in ameliorating submandibular salivary gland alterations in streptozotocin-induced diabetic rats.

Diabetes mellitus is a challenging health problem. Salivary gland dysfunction is one of its complications. Current treatments possess numerous adverse effects. Therefore, herbal extracts have emerged as a promising approach for safe and effective treatment. However, they are required in large doses to achieve the desired effect. Accordingly, Origanum majorana extract (OE) was incorporated into nano-sized systems to enhance its biological effects at lower dosages. OE was standardized against rosmarinic acid (RA) and then loaded into nano-cubosomal (NC) systems via a 23 full-factorial design. Two optimum nano-systems at different drug loads (2.08 or 1.04 mg-RA/mL) were selected and assessed in vivo to compare their effects in streptozotocin-induced diabetic rats against conventional OE (2.08 mg-RA/mL). Blood glucose was evaluated weekly. Submandibular salivary glands were processed for histopathological examination and nuclear factor-erythroid 2-related factor 2 (Nrf2), Kelch-like ECH-associated protein 1 (Keap1), and p38-MAPK gene expression analysis. NC systems were successfully prepared and optimized where the optimum systems showed nano-sized vesicles (210.4-368.3 nm) and high zeta potential values. In vivo results showed a significant lower blood glucose in all treated groups, with an exceptional reduction with NC formulations. Marked histopathological improvement was observed in all OE-treated groups, with OE-NC4 (2.08 mg-RA/mL) demonstrating the best features. This was supported by RT-PCR; where the OE-NC4 group recorded the highest mean value of Nrf2 and the least mean values of Keap1 and p38-MAPK, followed by OE-NC3 and OE groups. In conclusion, OE-loaded NC enhanced the anti-hyperglycemic effect of OE and ameliorated diabetic gland alterations compared to conventional OE. Thus, cubosomal nano-systems could be anticipated as potential carriers for the best outcome with OE.

Hindering the Synchronization Between miR-486-5p and H19 lncRNA by Hesperetin Halts Breast Cancer Aggressiveness Through Tuning ICAM-1.

BACKGROUND: Recently, a novel crosstalk between non-coding RNAs (ncRNAs) has been casted. However, this has been seldom investigated in metastatic BC (mBC). H19 and miR-486-5p role in mBC are controversial. ICAM-1 is a recently recognized metastatic engine in mBC. Natural compounds were recently found to alter ncRNAs/target circuits. Yet, Hesperitin's modulatory role in altering such circuits has never been investigated in mBC. OBJECTIVE: The aim of this study is to investigate the impact of hesperitin on miR-486-5p/H19/ICAM-1 axis. METHODS: BC patients (n=20) were recruited in the study. Bioinformatic analysis was performed using different prediction softwares. MDA-MB-231 and MCF-7 cells were cultured and transfected using several oligonucleotides or treated with serial dilutions of hesperitin. RNA was extracted and gene expression analysis was performed using q-RT-PCR. ICAM-1 protein levels were assessed using human ICAM-1 Elisa Kit. Cytotoxic potential of hesperitin against normal cells was assessed by LDH assay. Several functional analysis experiments were performed such as MTT, colony forming and migration assays. RESULTS: The study showed that miR-486-5p and H19 had paradoxical expression profiles in BC patients. miR- 486-5p mimics and H19 siRNAs repressed ICAM-1 and halted mBC hallmarks. A novel crosstalk between miR- 486-5p and H19 was observed highlighting a bi-directional relationship between them. Hesperetin restored the expression of miR-486-5p, inhibited H19 lncRNA and ICAM-1 expression and selectively regressed mBC cell aggressiveness. CONCLUSION: miR-486-5p and H19 are inter-connected upstream regulators for ICAM-1 building up miR-486- 5p/H19/ICAM-1 axis that has been successfully tuned in mBC cells by hesperitin.

Increased Risks of Re-identification For Patients Posed by Deep Learning-Based ECG Identification Algorithms.

ECGs analysis is an important tool in cardiac diagnosis. ECG data also have the potential to be used as a biometric source that allows precise person identification similar to the widely used fingerprint and iris recognition techniques. However, this phenomenon also raises serious privacy concerns. In this study, we provide a complete, multi-step ECG identification algorithm using a private database of ECG recordings. We train and validate our AI model on approximately 40k patients which makes this study by far the largest research project in this field. Moreover, our best model attained an exceptionally high accuracy of 94.56%. In addition to discussing the general implications of the deployment of such systems related to privacy, for the first time, we also assess the accuracy of ECG-based identification for distinct heart condition groups (and combinations of such conditions) and the corresponding privacy implications. For instance, we discovered that in contrast to initial expectation that identification accuracy for healthy normal sinus rhythm should be the highest, the identification accuracy is higher for patients with sinus tachycardia or patients who are diagnosed with both ST changes and supraventricular tachycardia. This puts these patients at a higher risk of privacy issues due to re-identification. On the other hand, we observed that patients with premature ventricular contractions have an identification accuracy as low as 78.54%. The identification rate for patients with a pacemaker is 80.2%.Clinical relevance-While ECG as a biometric can be a potentially useful technology, it also raises serious concerns regarding the privacy of cardiac patients. Especially, the ECG Identification algorithms empowered by deep learning can increase the risk of re-identification.

A High-Precision Machine Learning Algorithm to Classify Left and Right Outflow Tract Ventricular Tachycardia.

INTRODUCTION: Multiple algorithms based on 12-lead ECG measurements have been proposed to identify the right ventricular outflow tract (RVOT) and left ventricular outflow tract (LVOT) locations from which ventricular tachycardia (VT) and frequent premature ventricular complex (PVC) originate. However, a clinical-grade machine learning algorithm that automatically analyzes characteristics of 12-lead ECGs and predicts RVOT or LVOT origins of VT and PVC is not currently available. The effective ablation sites of RVOT and LVOT, confirmed by a successful ablation procedure, provide evidence to create RVOT and LVOT labels for the machine learning model. METHODS: We randomly sampled training, validation, and testing data sets from 420 patients who underwent successful catheter ablation (CA) to treat VT or PVC, containing 340 (81%), 38 (9%), and 42 (10%) patients, respectively. We iteratively trained a machine learning algorithm supplied with 1,600,800 features extracted via our proprietary algorithm from 12-lead ECGs of the patients in the training cohort. The area under the curve (AUC) of the receiver operating characteristic curve was calculated from the internal validation data set to choose an optimal discretization cutoff threshold. RESULTS: The proposed approach attained the following performance: accuracy (ACC) of 97.62 (87.44-99.99), weighted F1-score of 98.46 (90-100), AUC of 98.99 (96.89-100), sensitivity (SE) of 96.97 (82.54-99.89), and specificity (SP) of 100 (62.97-100). CONCLUSIONS: The proposed multistage diagnostic scheme attained clinical-grade precision of prediction for LVOT and RVOT locations of VT origin with fewer applicability restrictions than prior studies.

An acetylated derivative of vitexin halts MDA-MB-231 cellular progression and improves its immunogenic profile through tuning miR- 20a-MICA/B axis.

The activating immune ligands, MICA/B, act as a "kill me" signal through the NKG2D receptor expressed on natural killer (NK) cells. Recently, the oncogenic miR-20a was found to mediate immune escape through repressing MICA/B levels in breast cancer (BC) cells. However, targeting miR-20a-MICA/B using natural compounds has rarely been investigated. Our group has successfully isolated 3'-O-acetylvitexin that showed cytotoxic effects against colon cancer cells but has never been evaluated in BC. Our aim is to investigate the effects of 3'-O-acetylvitexin on BC cell lines and to further elucidate its molecular mechanism of action.The results showed that 3'-O-acetylvitex depicted a more pronounced dose-dependent repression of TNBC cellular viability, colonogenicity and migration capacity than Vitexin. 3'-O-acetylvitexin treatment resulted in a marked dose-dependent repression of miR-20a with a concomitant dose-dependent increase in MICA/B expression. In conclusion, 3'-O-acetylvitexin might act as a promising therapeutic agent for TNBC patients.

Flavonol Glycosides: In Vitro Inhibition of DPPIV, Aldose Reductase and Combating Oxidative Stress are Potential Mechanisms for Mediating the Antidiabetic Activity of Cleome droserifolia.

Diabetes is a major health problem that is associated with high risk of various complications. Medicinal plants hold great promise against diabetes. The traditional use of Cleome droserifolia as an antidiabetic agent was correlated to its flavonol glycosides content. In the current study, five major flavonol glycosides appeared on the RP-HPLC chromatogram of the aqueous extract namely; quercetin-3-O-ß-d-glucosyl-7-O-α-rhamnoside (1), isorhamnetin-7-O-ß-neohesperidoside (2), isorhamnetin-3-O-ß-d-glucoside (3) kaempferol-4'-methoxy-3,7-O-α-dirhamnoside (4), and isorhamnetin-3-O-α-(4″-acetylrhamnoside)-7-O-α-rhamnoside (5). The inhibitory activities of these compounds were tested in vitro against several enzymes involved in diabetes management. Only the relatively less polar methoxylated flavonol glycosides (4, 5) showed mild to moderate α-amylase and α-glucosidase inhibitory activities. Compounds 1-4 displayed remarkable inhibition of dipeptidyl peptidase IV (DPPIV) enzyme (IC50 0.194 ± 0.06, 0.573 ± 0.03, 0.345 ± 0.02 and 0.281 ± 0.05 µg/mL, respectively) comparable to vildagliptin (IC50 0.154 ± 0.02 µg/mL). Moreover, these compounds showed high potential in preventing diabetes complications through inhibiting aldose reductase enzyme and combating oxidative stress. Both isorhamnetin glycoside derivatives (2, 3) exhibited the highest activities in aldose reductase inhibition and compound 2 (IC50 5.45 ± 0.26 µg/mL) was even more potent than standard quercetin (IC50 7.77 ± 0.43 µg/mL). Additionally, these flavonols exerted excellent antioxidant capacities through 2, 2-diphenyl-1-picrylhydrazil (DPPH) and ferric reducing antioxidant (FRAP) assays.

Optimal Multi-Stage Arrhythmia Classification Approach.

Arrhythmia constitutes a problem with the rate or rhythm of the heartbeat, and an early diagnosis is essential for the timely inception of successful treatment. We have jointly optimized the entire multi-stage arrhythmia classification scheme based on 12-lead surface ECGs that attains the accuracy performance level of professional cardiologists. The new approach is comprised of a three-step noise reduction stage, a novel feature extraction method and an optimal classification model with finely tuned hyperparameters. We carried out an exhaustive study comparing thousands of competing classification algorithms that were trained on our proprietary, large and expertly labeled dataset consisting of 12-lead ECGs from 40,258 patients with four arrhythmia classes: atrial fibrillation, general supraventricular tachycardia, sinus bradycardia and sinus rhythm including sinus irregularity rhythm. Our results show that the optimal approach consisted of Low Band Pass filter, Robust LOESS, Non Local Means smoothing, a proprietary feature extraction method based on percentiles of the empirical distribution of ratios of interval lengths and magnitudes of peaks and valleys, and Extreme Gradient Boosting Tree classifier, achieved an F1-Score of 0.988 on patients without additional cardiac conditions. The same noise reduction and feature extraction methods combined with Gradient Boosting Tree classifier achieved an F1-Score of 0.97 on patients with additional cardiac conditions. Our method achieved the highest classification accuracy (average 10-fold cross-validation F1-Score of 0.992) using an external validation data, MIT-BIH arrhythmia database. The proposed optimal multi-stage arrhythmia classification approach can dramatically benefit automatic ECG data analysis by providing cardiologist level accuracy and robust compatibility with various ECG data sources.