Enhanced predictive modeling of dissolved oxygen concentrations in riverine systems using novel hybrid temporal pattern attention deep neural networks.

Monitoring water quality and river ecosystems is vital for maintaining public health and environmental sustainability. Over the past decade, data-driven methods have been extensively used for river water quality modeling, including dissolved oxygen (DO) concentrations. Despite advancements, challenges persist regarding accuracy, scalability, and adaptability of data-driven models to diverse environmental conditions. Previous studies primarily employed singular models or basic combinations of machine learning techniques, lacking advanced integration of adaptive mechanisms to process complex and evolving datasets. The current study introduces innovative hybrid models that integrate temporal pattern attention (TPA) mechanisms with advanced neural networks, including feed-forward neural networks (FFNNs) and long short-term memory networks (LSTMs). This approach leverages the synergistic strengths of individual models, significantly enhancing the accuracy of DO predictions. The models were rigorously tested against water quality data obtained from two distinct riverine environments, the Illinois River (ILL) and Des Plaines River (DP). Daily measured water quality data, including DO, chlorophyll-a, nitrate plus nitrite, water temperature, specific conductance, and pH, from 2017 to 2024 provided a robust foundation for comprehensive analysis of DO dynamics in these rivers. We conducted 10 scenarios with different model inputs, wherein the hybrid TPACWRNN-LSTM-10 model particularly excelled, achieving coefficient of determination values of 0.993 and 0.965, and root mean squared errors of 0.241 mg/L and 0.450 mg/L for DO predictions at the ILL and DP stations, respectively. The model's reliability was further confirmed by Willmott's index values of 0.998 and 0.992 and Nash-Sutcliffe efficiency values of 0.990 and 0.961 at the ILL and DP stations, respectively. Additionally, Shapley additive explanations (SHAP) values were utilized to interpret each predictor's contribution, revealing key drivers of DO predictions. We believe the novel hybrid modeling approach presented in this study could benefit utilities and water resource management systems for predicting water quality in complex systems.

Investigation of kinetics and absorption isotherm models for hydroponic phytoremediation of waters contaminated with sulfate.

Two common wetland plants, Pampas Grass (Cortaderia selloana) and Lucky Bamboo (Dracaena sanderiana), were used in hydroponic cultivation systems for the treatment of simulated high-sulfate wastewaters. Plants in initial experiments at pH 7.0 removed sulfate more efficiently compared to the same experimental conditions at pH 6.0. Results at sulfate concentrations of 50, 200, 300, 600, 900, 1200, 1500 and 3000 mg/L during three consecutive 7-day treatment periods with 1-day rest intervals, showed decreasing trends of both removal efficiencies and uptake rates with increasing sulfate concentrations from the first to the second to the third 7-day treatment periods. Removed sulfate masses per unit dry plant mass, calculated after 23 days, showed highest removal capacity at 600 mg/L sulfate for both plants. A Langmuir-type isotherm best described sulfate uptake capacity of both plants. Kinetic studies showed that compared to pseudo first-order kinetics, pseudo-second order kinetic models slightly better described sulfate uptake rates by both plants. The Elovich kinetic model showed faster rates of attaining equilibrium at low sulfate concentrations for both plants. The dimensionless Elovich model showed that about 80% of sulfate uptake occurred during the first four days' contact time. Application of three 4-day contact times with 2-day rest intervals at high sulfate concentrations resulted in slightly higher uptakes compared to three 7-day contact times with 1-day rest intervals, indicating that pilot-plant scale treatment systems could be sized with shorter contact times and longer rest-intervals.

Costs of hospital-acquired infection for patients hospitalized in intensive care unit of an Iranian referral hospital.

Background: Hospital infections have affected millions of people around the world and are considered as one of the most important issues related to patient safety. Therefore, this study was conducted to estimate the extra costs caused by hospital-acquired infections in hospitals. Methods: This retrospective cohort study was conducted in Tehran province, Iran, in 2017. Medical records of 235 patients hospitalized in one of Tehran hospitals were reviewed for the study. They were divided into case (90 patients) and control (145 patients) groups. Data were analyzed using SPSS and STATA software. Results: Results revealed no significant relationship between age and gender with the incidence of nosocomial infection (p>0.05). However, the chance of nosocomial infection is most affected by length of hospital stay and costs paid by patients. Moreover, nosocomial infection increases the length of hospital stay up to 25 days. Our results revealed that the mean±SD hospital stay of infected and non-infected patients were 15.8±17.2 and 40.8±19.1 days, respectively. Furthermore, the total cost of patients without any hospital infection was 2451±3098 USD (83 674 480±105 765 500 Rials). On the other hand, the cost for infected patients was 3264±6078 USD (207 497 500±111 430 700 Rials). Conclusion: Hospital-acquired infections can impose great costs on both patients and the health system. The results of this study indicated the importance of taking specific measures for infection control in hospitals.

Mutation patterns in small cell and non-small cell lung cancer patients suggest a different level of heterogeneity between primary and metastatic tumors.

Several studies have shown heterogeneity in lung cancer, with parallel existence of multiple subclones characterized by their own specific mutational landscape. The extent to which minor clones become dominant in distinct metastasis is not clear. The aim of our study was to gain insight in the evolution pattern of lung cancer by investigating genomic heterogeneity between primary tumor and its distant metastases. Whole exome sequencing (WES) was performed on 24 tumor and five normal samples of two small cell lung carcinoma (SCLC) and three non-SCLC (NSCLC) patients. Validation of somatic variants in these 24 and screening of 33 additional samples was done by single primer enrichment technology. For each of the three NSCLC patients, about half of the mutations were shared between all tumor samples, whereas for SCLC patients, this percentage was around 95. Independent validation of the non-ubiquitous mutations confirmed the WES data for the vast majority of the variants. Phylogenetic trees indicated more distance between the tumor samples of the NSCLC patients as compared to the SCLC patients. Analysis of 30 independent DNA samples of 16 biopsies used for WES revealed a low degree of intra-tumor heterogeneity of the selected sets of mutations. In the primary tumors of all five patients, variable percentages (19-67%) of the seemingly metastases-specific mutations were present albeit at low read frequencies. Patients with advanced NSCLC have a high percentage of non-ubiquitous mutations indicative of branched evolution. In contrast, the low degree of heterogeneity in SCLC suggests a parallel and linear model of evolution.

Integrating impacts of climate change on aquatic environments in inter-basin water regulation: Establishing a critical threshold for best management practices.

Inter-basin water diversion (IBWD) is a viable strategy to tackle water scarcity and quality degradation due to climate change and increasing water demand in headwaters regions. Nevertheless, the capacity of IBWD to mitigate the impacts of climate change on water quality has rarely been quantified, and the underlying processes are not well understood. Therefore, this study aims to elucidate how the IBWD manipulated total phosphorus (TP) loading dilution and conveying patterns under climate change and determine a critical threshold for the quantity of water entering downstream reservoirs (WIN) for operational scheduling. To resolve this issue, climate-driven hydrologic variability over a 60-year period was derived utilizing the least square fitting approach. Subsequently, six scenarios evaluating the response of in-lake TP concentrations (TPL) to increased temperatures and IBWDs of 50 %, 100 %, and 150 % from the baseline water volume in 2030 and 2050 were studied by employing a calibrated hydrological-water quality model (SWAT-YRWQM). In the next stage, three datasets derived from mathematical statistics based on the observed data, the Vollenweider formula, and modeled projections were integrated to formulate best management practices. The results revealed that elevated air temperatures would lead to reduced annual catchment runoff but increased IBWD. Additionally, our study quantified the IBWD potential for mitigating water quality degradation, indicating the adverse effects of climate change on TPL would be weakened by 4.2-14.4 %. A critical threshold for WIN was also quantified at 617 million m3, maintaining WIN at or near 617 million m3 through optimized operational scheduling of IBWD could effectively restrict external inflow TP loading to lower levels. This study clearly illustrates the intricate interactive effects of climate change and IBWD on aquatic environments. The methodology elucidated in this study for determining the critical threshold of WIN could be applied in water management for analogous watershed-receiving waterbody systems.

Apoptotic effect of melatonin on ER-positive breast cancer cell lines: ADGRL4 gene expression and promoter methylation.

Breast cancer (BC) is the second most common malignancy worldwide. ADGRL4, as a modulator of angiogenesis, undergoes various epigenetic modifications affecting its biological functions. In this study, we aimed to assess ADGRL4 promoter methylation status and its expression levels in primary breast tumors and to evaluate its potency as a plausible prognostic biomarker in BC. Furthermore, we evaluated the effect of melatonin on ADGRL4 expression and viability of BC cells in vitro. One hundred breast tumor tissue samples and adjacent non-tumor tissues were collected, followed by DNA isolation, bisulfite conversion, qRT-PCR, qMSP assay, and immunoblotting. In addition, four BC cell lines were treated with melatonin and subjected to ADGRL4 expression analysis and apoptosis assay. We found a significant correlation between ADGRL4 expression levels and HER2 status and stage of disease (P < 0.05). We observed a substantial attenuation in ADGRL4 promoter methylation in tumor samples compared to marginal non-tumor samples. A significantly lower expression of ADGRL4 was detected in two BC cell lines in the presence of melatonin. MCF-7 and BT474 melatonin-treated cell lines showed a significantly higher number of apoptotic cells than non-treated cells (P < 0.0001). Based on the receiver operating characteristic (ROC) curve analysis, ADGRL4 expression and ADGRL4 promoter methylation status showed moderate prognostic value. We found that melatonin has anti-cancer effects on BC cells. In addition, ADGRL4 expression can potentially be used as a prognostic biomarker in BC.

NEAT1 and CHROMR lncRNAs: a promising diagnostic tool for diffuse large B-cell lymphoma especially in elderly patients.

Background: Long non-coding (lnc) RNAs have crucial regulatory roles in molecular pathways, and their dysregulation is associated with the pathogenesis of malignancies such as Diffuse large B-cell lymphoma (DLBCL). Therefore, we aimed to study the NEAT1 and CHROMR expression in DLBCL and explore their association with clinicopathological characteristics.Methods & materials: DLBCL and non-tumor lymph node specimens were obtained to assess the expression levels.Results: NEAT1 and CHROMR expressions were significantly increased in DLBCL, and were linked with the age of DLBCL patients (aged >60). NEAT1 and CHROMR overexpression may serve as moderate-to-good diagnostic biomarkers, with NEAT1 and CHROMR exhibiting area under the curve values of 0.781 and 0.831, respectively.

[Box: see text].

Teaching Medical Professionalism with a Scenario-based Approach Using Role-Playing and Reflection: A Step towards Promoting Integration of Theory and Practice.

Introduction: Professionalism, as one of the core competencies of physicians, is essential for providing the patients with higher quality care. It is an abstract concept and its education and assessment need objective and operational methods. The present study aimed at teaching the concepts of professionalism based on a scenario-based approach using role-playing and reflection. Methods: This is a pre-experimental study (one-group pretest-posttest design) with a mixed method approach. The study was conducted on 18 medical students (by voluntary sampling method) who had enrolled in the Medical Ethics Course at Kashan University of Medical Sciences in 2020. Twelve scenarios were designed about the most prevalent issues of medical professionalism. In each session, one group of students played out their scenarios and then, the participants and instructors discussed their role-playing. Participants' knowledge about professionalism was assessed at the beginning and end of each session, and they completed a satisfaction questionnaire and a reflection form. T-tests (one-sample and paired T-test) were applied for statistical analysis. Quantitative and qualitative data were analyzed using SPSS software (version 26), and P<0.05 was considered statistically significant. Conventional content analysis was used to analyze the qualitative data. Results: The mean scores of the participants' knowledge in post-test were significantly higher than those in the pre-test (P=0.042, t=-2.074). The mean scores of the participants' role-playing quality (p<0.001) and satisfaction (p=0.001) were significantly higher than their corresponding test values. Qualitative analysis of the participants' reflections revealed their satisfaction with the study intervention. Conclusion: The scenarios, role-playing, and reflection could provide an opportunity for operationalizing the concepts of professionalism and deep learning of students. Medical instructors need to improve their knowledge and skills of using active methods in teaching professionalism to medical students.

Development and validation of a nomogram model for lung cancer based on radiomics artificial intelligence score and clinical blood test data.

Background: Artificial intelligence (AI) discrimination models using single radioactive variables in recognition algorithms of lung nodules cannot predict lung cancer accurately. Hence, we developed a clinical model that combines AI with blood test variables to predict lung cancer. Methods: Between 2018 and 2021, 584 individuals (358 patients with lung cancer and 226 individuals with lung nodules other than cancer as control) were enrolled prospectively. Machine learning algorithms including lasso regression and random forest (RF) were used to select variables from blood test data, Logistic regression analysis was used to reconfirm the features to build the nomogram model. The predictive performance was assessed by performing the receiver operating characteristic (ROC) curve analysis as well as calibration, clinical decision and impact curves. A cohort of 48 patients was used to independently validate the model. The subgroup application was analyzed by pathological diagnosis. Findings: A total of 584 patients were enrolled (358 lung cancers, 61.30%,226 patients for the control group) to establish the model. The integrated model identified eight potential factors including carcinoembryonic antigen (CEA), AI score, Pro-Gastrin Releasing Peptide (ProGRP), cytokeratin 19 fragment antigen21-1(CYFRA211), squamous cell carcinoma antigen(SCC), indirect bilirubin(IBIL), activated partial thromboplastin time(APTT) and age. The area under the curve (AUC) of the nomogram was 0.907 (95% CI, 0.881-0.929). The decision and clinical impact curves showed good predictive accuracy of the model. An AUC of 0.844 (95% CI, 0.710 - 0.932) was obtained for the external validation group. Conclusion: The nomogram model integrating AI and clinical data can accurately predict lung cancer, especially for the squamous cell carcinoma subtype.

Melatonin administration during the first half of pregnancy improves the reproductive performance of rabbits: Emphasis on ovarian and placental functions.

This study was designed to investigate the roles of melatonin administration during different sensitive windows of the first half of pregnancy in the function and gene expression of the ovary and placenta, hormone profile, and pregnancy outcomes in rabbits. Four equal experimental groups of 20 rabbits each were used. The first (FW), second (SW), and third (F + SW) groups comprised rabbits that orally received 0.7-mg melatonin/kg body weight during the first week, second weeks, and during both weeks of pregnancy; and the fourth group served as the control group (C). The total number of visible follicles significantly increased in all melatonin-treated groups compared with that in the C group. In all melatonin-treated groups, the number of absorbed fetuses was significantly reduced, whereas the weights of embryonic sacs and fetuses were higher than in the C group. The placenta efficiency was significantly increased in the F + SW group compared with that in the C group, followed by the SW group, whereas no significant difference in the placenta efficiency was found between the FW and C groups. Melatonin treatments significantly improved the expression of antioxidants, gonadotropin receptors, and cell cycle regulatory genes in the ovary, whereas only FW treatment upregulated steroidogenic acute regulatory gene. Compared with the C and FW groups, melatonin treatments during the SW and F + SW significantly upregulated the expression of most genes in the placenta. The concentrations of estradiol were significantly higher in the SW and F + SW groups than in the FW and C groups. The concentrations of progesterone were significantly increased in the FW group compared with those in the C and SW groups, whereas the F + SW group showed intermediate values. The litter size and weight at birth significantly increased in all melatonin-treated groups compared with those in the C group. The second week of pregnancy seems to be a sensitive window for melatonin actions during pregnancy. Thus, melatonin administration during the second week of pregnancy can be effective in improving pregnancy outcomes in rabbits.

Moderate Prognostic Value of lncRNA FOXD2-AS1 in Gastric Cancer with Helicobacter pylori Infection.

PURPOSE: Gastric cancer (GC) is one of the most frequent tumors worldwide and identification of a sensitive and specific prognostic biomarker is of great importance. Long non-coding RNAs (lncRNAs) play crucial roles in tumorigenesis of various malignancies. In the present study, we investigated lncRNA FOXD2-AS1 expression in gastric tumors and assessed its potential as a prognostic biomarker. METHODS: A total of 95 tumor and corresponding adjacent non-tumor tissue specimens were collected from patients with GC from Imam Reza hospital, Tabriz, Iran. Total RNA was isolated and FOXD2-AS1 expression was measured using quantitative reverse transcriptase (qRT)-PCR. RESULTS: FOXD2-AS1 was significantly upregulated in tumor samples as compared to non-tumor tissues (P < 0.0001). In addition, higher expression of FOXD2-AS1 was significantly associated with lymph node metastasis and Helicobacter pylori infection. The receiver operating characteristic (ROC) curve analysis revealed that FOXD2-AS1 might be served as a potential prognostic biomarker for GC. CONCLUSION: FOXD2-AS1 is upregulated in gastric tumors and can be used as a valuable biomarker in the prognosis of patients with GC.

Expression of lncRNAs AK058003 and APOC1P1 in breast cancer patients.

In the current study, the expression levels of two important lncRNAs, i.e., AK058003 and APOC1P1, in breast tumors were compared with adjacent non-tumor tissues to evaluate their diagnostic potential in a panel of 121 patients. Total RNA was extracted, cDNA was synthesized and expression of AK058003 and APOC1P1 was assessed using qRT-PCR. A significant overexpression and positive correlation between these two lncRNAs were observed in tumor tissues compared to marginal healthy tissues. In conclusion, the examined lncRNAs were overexpressed in tumor tissues, suggesting their significant diagnostic value in breast cancer.

Ectopic expression of lncRNA MVIH as a potential diagnostic biomarker in cervical cancer.

AIM: Cervical cancer (CC) is one of the most common cancers in women. Recent advances in screening and vaccination against the papilloma virus (HPV) have increased protection against CC. However, there is no effective diagnostic biomarker and treatment approach during the course of the disease. The current study is thus aimed to evaluate the changes in the expression of lncRNA associated with microvascular invasion in hepatocellular carcinoma (lncRNA MVIH) and its diagnostic value as a biomarker in CC patients. MATERIALS AND METHODS: One-hundred and fifteen (n = 115) pairs of CC primary tumor and marginal non-tumor tissue samples were obtained from Tabriz Valiasr International Hospital (Tabriz, Iran). RNA extraction and cDNA synthesis followed by quantitative reverse transcriptase PCR (qRT-PCR) were considered to investigate alterations in the expression levels of MVIH in patients with CC. The associations between MVIH expression changes and clinicopathological features as well as its potential as a diagnostic biomarker were assessed using SPSS and GraphPad prism software and the receiver operating characteristic (ROC). RESULTS: The expression levels of MVIH were significantly higher in CC tumors as compared to marginal non-tumor samples (p < 0.0001). Overexpression of MVIH was significantly associated with younger age (p = 0.033), lymph node metastasis (p = 0.031), tumor invasion depth (p = 0.035), and squamous cell type of CC (p = 0.019). The ROC analysis for MVIH as a diagnostic biomarker revealed the respective sensitivity and specificity of 67.83 and 80. CONCLUSIONS: Overexpression of MVIH in CC tumors suggests its oncogenic role during tumorigenesis. Thus, it may serve as a potential diagnostic biomarker.

Prognostic Value of LncRNA KRT18P55 in Patients with Intestinal Type of Gastric Cancer.

PURPOSE: Gastric cancer (GC) is a heterogeneous disease, and this heterogeneity significantly affects survival and treatment outcomes. Identification of molecular biomarkers specific for early-stage GC can help clinicians to choose more precise and effective treatment approaches. Long non-coding RNAs (lncRNAs) have the potential to be used as biomarkers because of their tissue specificity, stability, and availability in body fluids. In this study, we aimed to investigate changes in the expression levels of lncRNA KRT18P55 and to assess its biomarker potentials in patients with GC. METHODS: Tumor and non-tumor marginal tissues were collected from 102 patients at Noor-Nejat Hospital (Tabriz, Iran). RNA was isolated, and quantitative reverse transcriptase PCR (qRT-PCR) was performed to assess KRT18P55 expression levels in tumor and non-tumor tissue samples. The receiver operating characteristic (ROC) curve analysis was performed to evaluate potentials of KRT18P55 as a prognostic biomarker in GC. SPSS and GraphPad Prism software were used for data analysis. RESULTS: We found that KRT18P55 is significantly overexpressed in tumor as compared to non-tumor tissues (p < 0.0001). We found a significant association between KRT18P55 overexpression and intestinal GC subtype (p < 0.0001), lymph node metastasis (p = 0.013), and Helicobacter pylori infection (p = 0.033). Based on the ROC analysis, KRT18P55 showed a sensitivity and specificity of 53.92% and 77.45%, respectively. CONCLUSION: Overexpression of KRT18P55 in gastric tumors is suggestive of its oncogenic role in GC. In addition, KRT18P55 may be used as a potential prognosis biomarker and therapeutic target in intestinal GC subtype.

Characterization, in-silico, and in-vitro study of a new steroid derivative from Ophiocoma dentata as a potential treatment for COVID-19.

The medicinal potential of marine invertebrates' bioactive components that may act as anti-COVID-19 demonstrated promising results. Ophiocoma dentata, which is common in the Red Sea, is one such source. Therefore, this study aimed to isolate a new compound from the brittle star, Ophiocoma dentata, and evaluate its efficacy as anti-COVID-19 in-silico and in-vitro. Standard procedures were followed in order to assess the isolated compound's preliminary toxicity and anti-inflammatory properties. Computer virtual screening technology through molecular docking and ADMET studies was conducted as well as a new steroid derivative was isolated for the first time, named 5α-cholesta-4(27), 24-dien-3ß, 23 ß-diol. Investigation of the Anti-Covid-19 activity of the isolated compound using a Plaque reduction assay revealed 95% inhibition at a concentration of 5 ng/µl (12.48 µM). Moreover, this compound showed an IC50 of 11,350 ± 1500 ng/ml against the normal fibroblast cells, indicating its safety. Interestingly, this compound exhibited anti-inflammatory activity with an IC50 of 51.92 ± 0.03 µg/ml compared to a reference drug's IC50 of 53.64 ± 0.01 µg/ml, indicating that this compound is a potent anti-inflammatory. In silico data have proved that the isolated compound is a promising viral inhibitor against SARS-CoV2 and is thus recommended as a future nature preventive and curative antiviral drug.

Effects of heavy metal contamination released by petrochemical plants on marine life and water quality of coastal areas.

The present study attempts to assess the threat of water contamination in Persian Gulf by heavy metals (Fe, Cr, Pb, Cu, Zn, Cd, Se, and Ni) and its subsequent effects on five fish species including Scomberomorus guttatus (S. guttatus), Lethrinus nebulosus (L. nebulosus), Brachirus orientalis (B. orientalis), Pomadasys kaakan (P. kaakan), and Scomberomorus commerson (S. commerson). Water and fish samples from fourteen monitoring stations were obtained to determine the concentrations of contaminants in water and fish. Heavy metal pollution index (HMPI) and non-carcinogenic hazard quotient (NHQI) were employed to evaluate contamination level in water and fish muscle. The Kriging geostatistical method was employed to determine the spatial distribution of different heavy metals around petrochemical plants. The highest NHQI values for P. kaakan and B. orientalis species were 1.036 and 1.046, respectively. In both cases, the NHQI values were higher than the maximum allowable value of 1, indicating that both fish species were on the verge of contamination by heavy metals, which in turn makes the consumption of these fish highly hazardous to human health. The lowest NHQI value was observed in S. commerson species at a value of 0.394, indicating its harmlessness to human health. Overall, fish species living within the top 5 m of the water column (S. commerson and S. guttatus) were found to be less contaminated by heavy metals compared to species dwelling near the seafloor (P. kaakan and B. orientalis). Results also indicated the pollution absorption rate in S. commerson and S. guttatus were 0.45 and 3.4 mg/kg-year, while the corresponding values for the B. orientalis and L. nebulosus species were 6 and 2 mg/kg-year, respectively. P. kaakan species showed a pollution absorption rate of 3.2 mg/kg-year. High heavy metal concentrations of 4.8, 10, 9.8, 5.2, 9.4, and 6.7 mg/L were obtained for Cr, Zn, Pb, Ni, Fe, Cu, and Cd, respectively, in water samples obtained from stations nearby petrochemical plants. The HMPI index for the most contaminated stations was ten times that of the maximum allowable limit. Given the intense activity of oil, gas, and petrochemical plants in the Persian Gulf, defining safe fishing areas by management practices similar to contamination zoning maps presented in this study can substantially protect the public health from heavy metal contamination.

Cancer driver gene and non-coding RNA alterations as biomarkers of brain metastasis in lung cancer: A review of the literature.

Brain metastasis (BM) is the most common event in patients with lung cancer. Despite multimodal treatments and advances in systemic therapies, development of BM remains one of the main factors associated with poor prognosis and mortality in patients with lung cancer. Therefore, better understanding of mechanisms involved in lung cancer brain metastasis (LCBM) is of great importance to suppress cancer cells and to improve the overall survival of patients. Several cancer-related genes such as EGFR and KRAS have been proposed as potential predictors of LCBM. In addition, there is ample evidence supporting crucial roles of non-coding RNAs (ncRNAs) in mediating LCBM. In this review, we provide comprehensive information on risk assessment, predictive, and prognostic panels for early detection of BM in patients with lung cancer. Moreover, we present an overview of LCBM molecular mechanisms, cancer driver genes, and ncRNAs which may predict the risk of BM in lung cancer patients. Recent clinical studies have focused on determining mechanisms involved in LCBM and their association with diagnosis, prognosis, and treatment outcomes. These studies have shown that alterations in EGFR, KRAS, BRAF, and ALK, as the most frequent coding gene alterations, and dysregulation of ncRNAs such as miR-423, miR-330-3p, miR-145, piR-651, and MALAT1 can be considered as potential biomarkers of LCBM.

Key Epigenetic Events Involved in the Maintenance of Breast Cancer Stem Cells.

BACKGROUND: Cancer stem cells (CSCs) are a small subpopulation of cells within tumors and play significant roles in tumorigenesis, metastasis, resistance to treatment, and relapse. They are defined by self-renewal and multi-lineage differentiation, and aggressiveness. Epigenetic modifications, including DNA methylation and acetylation, histone modifications, and non-coding. RNAs (ncRNAs), are partly responsible for CSC potentials and are involved in the modification of key components of crucial pathways such as Notch and Wnt signaling in breast cancer. OBJECTIVE: In this review, we present an overview of the pathways and epigenetic events that lead to the transformation of mammary gland stem cells to breast CSCs (BCSCs). Based on the data presented here, important pathways such as TGF-ß/SMAD2 and Wnt/ß-catenin and epigenetic modifications, including histone modifications, DNA methylations, and microRNAs, play important roles in BCSC formation and maintenance. CONCLUSION: Epigenetic events can alter the expression of genes and functional RNAs, resulting in tumor initiation and progression. Thus, a better understanding of epigenetic modifications involved in BCSC maintenance signaling pathways may help to eliminate or suppress BCSCs and overcome cancer by generating more effective and efficient therapeutic agents.

Nanoparticles of ZnO/Berberine complex contract COVID-19 and respiratory co-bacterial infection in addition to elimination of hydroxychloroquine toxicity.

Purpose: A novel coronavirus (COVID-19) that has not been previously identified in humans and has no specific treatment has recently spread. Treatment trials using antiviral and immune-modulating drugs such as hydroxychloroquine (HCQ) were used to control this viral outbreak however several side effects have emerged. Berberine (BER) is an alkaloid that has been reported to reveal some pharmacological properties including antioxidant and antimicrobial activities. Additionally, Zinc oxide nanoparticles (ZnO-NPs) possess potent antioxidant and anti-inflammatory properties. Therefore, this study was undertaken to estimate the efficiency of both BER and synthetic ZnO/BER complex as an anti-COVID-19 therapy. Methods: First, the ZnO/BER complex was prepared by the facile mixing method. Then in vitro studies on the two compounds were conducted including VeroE6 toxicity, anti-COVID-19 activity, determination of inhibitory activity towards papain-like proteinase (PL pro) and spike protein- and receptor- binding domain (RBD) as well as assessment of drug toxicity on RBCs. Results: The results showed that ZnO/BER complex acts as an anti-COVID-19 by inhibiting spike protein binding with angiotensin-converting enzyme II (ACE II), PL pro activity, spike protein and E protein levels, and expression of both E-gene and RNA dependent RNA polymerase (RdRp) at a concentration lower than that of BER or ZnO-NPs alone. Furthermore, ZnO/BER complex had antioxidant and antimicrobial properties where it prevents the auto oxidation of 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and the culture of lower respiratory system bacteria that affected Covid 19 patients. The ZnO/BER complex prevented as well the HCQ cytotoxic effect on both RBC and WBC (in vitro) and hepatotoxicity, nephrotoxicity and anemia that occurred after HCQ long administration in vivo. Conclusion: The ZnO/BER complex can be accounted as promising anti-COVID 19 candidate because it inhibited the virus entry, replication, and assembly. Furthermore, it could be used to treat a second bacterial infection that took place in hospitalized COVID 19 patients. Moreover, ZnO/BER complex was found to eliminate the toxicity of long-term administration of HCQ in vivo.

Effects of lake water level fluctuation due to drought and extreme winter precipitation on mixing and water quality of an alpine lake, Case Study: Lake Arrowhead, California.

Lake Arrowhead, an oligotrophic alpine lake in southern California, experienced a drought period from summer 2012 to winter 2018 followed by a season of intense storms in winter 2019 resulting in lake flooding. This study investigates the effects of seasonal variations combined with 3.5 m water level fluctuation from May 2018 to April 2019, on water quality and hydrodynamics of Lake Arrowhead. In-situ measured meteorological data and water quality profiles in five different bays were used to develop and calibrate a three-dimensional lake hydrodynamic model. The mean relative errors between simulated and measured temperature and salinity profiles were 6.1% and 4.2%, respectively. Root mean square errors between the measured and simulated water temperatures were slightly larger during the stratified period. However, no specific pattern was observed in error analysis of salinity simulations. Strong thermal stratification during summer and early-fall resulted in hypoxic hypolimnetic waters with dissolved oxygen (DO) concentrations of <1 mg L-1. Turbulent kinetic energy (TKE) generated by convective motions in the water column due to surface heat loss was typically more than two times greater than the wind-induced mixing energy during the stratification period. The lake experienced an energetic turbulent mixing regime with TKE fluxes >1.5 m-3 s-3, and Lake numbers <0.1 during the winter cooling period, resulting in a complete water column turnover and resuspension of bottom sediments. Entrainment of the hypoxic hypolimnion layers and sediment resuspension resulted in decreased DO and pH in the water column from December 2018 through mid-January 2019. Comparisons of Wedderburn and Lake numbers during different stratification conditions indicated the same trends in the strong stratification period (square of buoyancy frequency >10-4 s-2). However, in other conditions, the Lake number, considering the lake bathymetry and density profile, could better reflect vertical mixing conditions.