Miracle-dz/UniFAR-FTUs huggingface dataset:
Abstract 916: A screen to target EGFR (C797S) in osimertinib-resistant lung cancer identifies brigatinib-based combinations that synergistically inhibit cell growth

Up to 20% of non small-cell lung cancers are driven by activating mutations in EGFR (EGFRm). While EGFR tyrosine kinase inhibitors (TKIs) have proven highly effective in the clinic (e.g. gefitinib in first line EGFRm and osimertinib in T790M post-TKI resistance), acquired resistance mechanisms present an obstacle to curing EGFR-driven disease. To-date, approximately 20% of osimertinib-resistant cases in the 2nd line setting are EGFRm/T790M/C797S, and there is currently no approved therapy for these “triple-mutant” (TM) patients. We have obsrerved that the ALK inhibitor brigatinib shows moderate, equipotent activity against both EGFR-TM and the single activating mutant. We used this information to screen a panel of compounds to identify brigatinib-based combinations that could effectively target EGFR-TM-expressing cells. Among the most potent combination partners were selumetinib and other inhibitors of the MAP kinase pathway. These agents were able to synergistically impair growth of TM cells when combined with brigatinib in vitro, and accordingly show prolonged suppression of downstream pathway biomarkers in combination- vs. brigatinib monotherapy-treated cells. Further, we have shown effective combinations can dramatically enhance apoptotic cell death compared to brigatinib treatment alone. Critically, neither monotherapy treatment with effective combination partners, nor combinations based on osimertinib showed growth inhibition in the EGFR triple-mutant setting. Taken together, these data suggest novel therapeutic strategies for patients in this critical area of unmet need that warrant further preclinical testing. Citation Format: Matthew J. Martin, Nicolas Floc9h, Chrysiis Michaloglou, M Raymond Finlay, Richard A. Ward, Paul D. Smith, Darren A. Cross. A screen to target EGFR (C797S) in osimertinib-resistant lung cancer identifies brigatinib-based combinations that synergistically inhibit cell growth [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 916.
Combination Therapy in Ischemic Stroke: Synergistic Neuroprotective Effects of Memantine and Clenbuterol

Background and Purpose— Although excitotoxic overactivation of glutamate receptors has been identified as a major mechanism of ischemic brain damage, glutamate receptor antagonists failed in stroke trials, in most cases because of limited therapeutic windows or severe adverse effects. Therefore, we chose memantine and clenbuterol, both approved safe and efficient in their respective therapeutical categories, and examined combinations of these neuroprotectants for possible therapeutic interactions in ischemic stroke. Methods— Combinations of the N-methyl-d-aspartate (NMDA) receptor antagonist memantine (20 mg/kg) with the β2-adrenoceptor agonist clenbuterol (0.3 to 3 mg/kg) were tested in a mouse model of permanent focal cerebral ischemia. In addition, combinations of memantine (1 to 10 nmol/L) and clenbuterol (1 to 10 nmol/L) were examined in cultured hippocampal neurons exposed to glutamate (500 μmol/L) or staurosporine (200 nmol/L). Results— The infarct size was further reduced by combination therapy as.
Improving Early Infant Feeding Practices with an Evidence Based Education Handout

Nearly half of all infants are introduced to solid food before the recommended age. The World Health Organization and American Academy of Pediatrics have established guidelines encouraging parents to delay solid food introduction until six months of age. Evidence indicates that introducing solid food prematurely can be problematic for infants because they may not be developmentally prepared and it can lead to an increase in infectious disease, atopic disease, and childhood obesity. The decision to introduce solid foods can be influenced by social support systems and advice from pediatric primary care providers. The purpose of this one group, quasiexperimental pretest-posttest design was to determine if evidence based infant feeding education improved parental intention to delay solid foods until six month of age in a primary care pediatric setting. Data collected using a modified Infant Feeding Intentions Scale (IFI) was used to compare parental intention to introduce solid food before and after the educational handout. Nine patients in a Des Moines, Iowa primary care pediatric clinic participated in the intervention provided by five pediatric providers. The results of this DNP project did not show an improvement in parental intent to delay solid food; however, the actual timing of solid food introduction was 5.5 months which is greater than the national average. Delaying solid food to infants can have a major impact on pediatric healthcare including a low incidence of comorbidities related to infectious diseases, atopic disease, and obesity and a decrease in healthcare costs associated with the comorbidities.
Cardiopulmonary Resuscitation Theoretical Knowledge Retention of Some Nigerian Teachers 15 Months after Initial Training

Introduction: For effective bystander cardiopulmonary resuscitation (CPR) to be achievable, potential bystander CPR providers must be able to retain sufficient CPR knowledge for a reasonable time frame after training. This study aimed at ascertaining the retained CPR theoretical knowledge of some Nigerian teachers after 15 months of CPR training. Materials and Methods: A quasi-experimental study design was used. From the initial cohort of forty one (41) teachers, thirty one (31) of them participated in the last phase of the study. The same self-administered questionnaire with seven (7) questions on their theoretical CPR knowledge, used initially immediately after their CPR training in 2016 to assess them was used again in December 2017 without further training. The data was analysed using both descriptive and paired samples t-test statistics. Results: Generally, the participants had good retention of the CPR theoretical knowledge that were not statistically significantly different from their post-training knowledge earlier (P > 0.05) except in two questions where the differences (CPR knowledge losses) were statistically significant (P < 0.05). Conclusions/ Recommendations: The Nigerian teachers retained satisfactory CPR theoretical knowledge after 15 months of initial training, which holds promise for their ability to provide bystander CPR for victims of out-of-hospital cardiac arrests (OHCAs) and the training of their students with the possible incorporation of CPR programme into Nigerian schools’ curricula. There is need to repeat the study with larger sample sizes.
Scalable multi-objective control for large scale water resources systems under uncertainty

Advances in modeling and control have always played an important role in supporting water resources systems planning and management. Changes in climate and society are now introducing additional challenges for controlling these systems, motivating the emergence of complex, integrated simulation models to explore key causal relationships and dependencies related to uncontrolled sources of variability. In this paper, we contribute a massively parallel implementation of the evolutionary multi-objective direct policy search method for controlling large scale water resources systems under uncertainty. The method combines direct policy search with nonlinear approximating networks and a hierarchical parallelization of the Borg Multi-Objective Evolutionary Algorithm. This computational framework successfully identiﬁes control policies that address both the presence of multidimensional tradeoffs and of severe uncertainties in the system dynamics and policy performance. We demonstrate the approach on a challenging real-world application, represented by the optimal control of a network of four multipurpose water reservoirs in the Red River basin in Northern Vietnam, under observed and synthetically generated hydrologic conditions. Results show that the reliability of the computational framework in ﬁnding near-optimal solutions increases with the number of islands in the adopted hierarchical parallelization scheme. This setting reduces the vulnerabilities of the designed solutions to the system’s uncertainty and improves the discovery of robust control policies addressing key system performance tradeoffs.
Improved Early Detection of Gestational Diabetes via Intelligent Classification Models: A Case of the Niger Delta Region in Nigeria

Diabetes is the most common endocrine-metabolic disorder that features a body characterized by hyperglycaemia – giving rise to risk of microvascular (retinopathy, neupathy and nephropathy) and microvascular (vascular disease, stroke and ischemic heart diseases). Nigeria has become aware of inherent threats of the Type-II diabetes and the consequent metamorphism into gestational diabetes in mothers with or without previous cases of Type-II. We presents a comparative study of classification models using both the supervised and unsupervised evolutionary models. We aim at improved early detection of the disorder via data-mining tools. Adopted dataset is from College of Health and Teaching Hospitals with selected Universities in Niger Delta. Results show that age, body mass index, family ties to second degree, environmental conditions of inhabitance among others are critical factors that increases its likelihood. Gestational diabetes in mothers were confirmed if: (a) history of babies weighing > 4.5kg at birth, (b) insulin resistance with polycystic ovary syndrome, and (c) abnormal tolerance to insulin.
Multivalued function recognition based on spectral clustering

In scientific research, bioinformatics, Internet applications, e-commerce and many other application fields, the amount of data is growing at an extremely fast rate. To analyze and utilize these huge data resources, it is necessary to rely on effective data analysis technology. Big data application is a process of mining effective information from big data by using data analysis methods, providing auxiliary decisions for users and realizing the value of big data. In the process of data calculation and analysis, we will often find that the data from the same source will show multiple function images in the same coordinate system, which will make the same variable correspond to multiple values in data prediction analysis. We call it multivalued function here. This paper provides a method to identify multivalued functions. By using the maximum information coefficient (MIC) theory proposed by David n. Reshef, and using the data sampling method to calculate the function identifiability of the data set, then, the spectral clustering method is used for recognition, segment and mark the images of different functions. Finally, the regression function equations with different marks are obtained by Gauss-newton iteration method. The results can be used for data prediction and analysis to assist decision-makers to make reasonable judgments.
ECMO use post DCD Heart Transplantation: A Retrospective Study

Method Between 2014 and 2017, 18 heart transplants were performed from DCD donors using machine perfusion (MP) for transport and resuscitation. Recipients were stratified into two groups based on early ECMO use. Donor data were collected using referral paperwork; retrieval data from local database and recipient data extracted from hospital medical records. Key donor and retrieval factors were identified and compared between the two groups (including. timing of withdrawal, MP duration), intraoperative details, and post-operative outcomes. Results 7 recipients required ECMO support post-operatively. Baseline demographics for donor and recipient between both groups were similar. The time interval between circulatory arrest (CA) and institution of cardioplegia was significantly longer in the ECMO group, due mainly to a longer delay between CA and knife to skin time when compared to non-ECMO group. Cold ischaemic time and time on MP were similar in both groups with poorer lactate recovery in the ECMO group when compared to the non ECMO group. Intraoperatively, ECMO group required longer bypass time and in the post-operative period require significantly longer stay in ICU. All recipients regained normal graft function and overall survival was 100% in both groups. Conclusion ECMO utility in our cohort appears to correlate with prolonged asystole to cardioplegia time, largely due to delays during transportation of donor to the operating table. This is associated with delayed graft recovery. However, all hearts were able to be recovered to normal cardiac function despite ECMO use, and there appears to be no impact on short term survival. Figure. No caption available.
Heuristic Evaluation of University Libraries’ Mobile Websites in Poland

Thesis/objective – the issue of evaluation of university mobile services has not been broadly explored, especially in Poland. Such research is worth conducting, as more and more users of library websites – students in particular – use mobile devices while searching required information. Mobile versions of university websites have not become very popular in Poland as of yet. Of the 10 largest university libraries of this kind, only 4 have a mobile version. The paper presents the evaluation of their quality and benchmarking with a view to identifying the best practices. Research method – the quality-heuristic method and benchmarking were used. The research questionnaire covered both the content as well as the functioning of the services. Results and conclusions – The service of the library of the University of Torun turned out to be the best; the remaining ones appeared to be a little less attractive mainly due to their limitations linked with information availability. None of the services, however, received the maximum score. Research results show the elements which still offer room for improvement.
Model and dynamical assessment of innovative potential in the face of the rapid emergence of competing innovative solutions and the expansion of the global information space

The article considers the currently relevant issue of achieving the organization of advanced development. Since, as a rule, the innovative development approach is the basis for managing the development of an organization, which suggests the implementation of projects for the development and production of advanced development in an enterprise, the focus is on assessing the organization’s innovative potential in the context of expanding the global information space. As a result of the innovation process carried out by the organization, there is not only the achievement of advanced development, but also the development of highly competitive products that form a new product market and radically change the existing market. Of course, to create a product that leads an organization to advanced development, it is necessary to have a number of resources and competencies discussed in the article. The example of the smartphone market, which characterized by a multidirectional change in the share occupied by the main manufacturers with similar innovative potential, is considered. As part of the mathematical model of Stackelberg, which describes the behavior of players in the oligopolistic market for high-tech products (as discussed in the article, the smartphone market), the game of several players-companies supplying their products to the market was considered.
Prevalence of ectopic pregnancy in Iran: a systematic review and meta-analysis

Introduction: Ectopic pregnancy is the most common causes of maternal mortality at first trimester of pregnancy. The mortality rate of this complication is about tenfold of vaginal delivery and five times more than induced abortion. The likelihood of success in the next pregnancy is also reduced, as well as this condition has a negative effect on mental state of the mother. The prevalence varies in different countries. This systematic study and meta-analysis was performed with aim to evaluate the prevalence of ectopic pregnancy in Iran. Methods: In this review article, databases includingPub MED, ISI, Google Scholar, Scopus and Iranian technical and scientific websites such as Magiran, Iranmedex, SID were searched using the keywords of â��ectopic pregnancyO� EPO� PrevalenceO� incidence, Iranâ�� and their equivalents in Persian up to 21 January 2016. In this meta-analysis on all existing literatures about the prevalence of ectopic pregnancy in Iran, 13 articles were found that based on inclusion criteria, 7 articles were selected that 5 of them in order to determine the prevalence of ectopic pregnancy in Iran and 2 in order to determine the prevalence of ectopic pregnancy in infertility centers were included in meta-analysis. Cochrane test was used to determine the homogeneity of samples. Prevalence was estimated based on Random effect in Revman software (version 5.3). Results: Prevalence of ectopic pregnancy before 2006 was estimated as 1.9 in 1000 pregnancies and after 2006 as 3.7 in 1,000 pregnancies and in infertility centers as 44 in 1000 pregnancies. Conclusion: Prevalence of ectopic pregnancy has increased in Iran in the past decade and infertility treatment is a risk factor for it.
Bone Mineral Density and Bone Turnover Markers in healthy Pre and Postmenopausal Women and the influence of multiple factors on them

AIM AND/ OBJECTIVES : To study Bone Mineral Density (BMD) and Bone Turnover Markers (BTMs) and factors influencing them in postmenopausal-women and their premenopausal-daughters and to study reference ranges of BTMs and their correlations with BMD. MATERIAL AND METHODS : This cross sectional study was conducted at an urban area in Vellore district. One hundred fifty two subjects which included 76 postmenopausal women and their daughters (n=76) who met the inclusion criteria were recruited from the community after obtaining a written informed consent. Details with regards to age, parity, dietary calcium intake, sunlight exposure and socioeconomic status, physical activity using “International Physical Activity Questionnaire” (IPAQ) and BMI were collected. Fasting blood and second void morning urine samples were obtained for measurement of BTMs (sCTX, sPTNP1, sOC and urine DPD respectively) and bone mineral parameters. BMD was measured by DXA. RESULTS : Osteoporosis was seen in 50% of the postmenopausal women and low bone mass was seen in 9% of daughters at spine. Ethnicity based reference range of BTMs were derived. Significant inverse correlation was found between BTMs and the BMD with good analytical performance (AUC>0.70, P <0.001) in the diagnosis of osteoporosis. Daughters born to mothers with osteoporosis at spine had lower BMD compared to daughters whose mothers did not have osteoporosis (P=0.047). Low socio-economic status (SES) was found to have a detrimental effect on BMD at spine (Odds 3.2, P=0.03). CONCLUSIONS: Osteoporosis was seen in half of the postmenopausal women and low bone mass seen in one tenth of the premenopausal women. The reference range for various BTMs was studied in a well-defined cohort of premenopausal women and their mothers. Lower SES was a significant risk factor for osteoporosis which highlights the importance of simple interventions to improve the peak bone mass and reduce the bone loss by optimising calcium and vitamin D intake, encouraging physical activity, awareness and allocation of resources for screening and treatment of osteoporosis in the community. In view of good analytical performance of BTMs in the diagnosis of osteoporosis and the cost effectiveness and ease of estimation of their assays, in future, it may be possible to use BTMs as a screening tool in osteoporosis. However, it needs further validation in larger studies.
On chassis predictive maintenance and service solutions: An unsupervised machine learning approach

Predictive maintenance is a key component in cost reduction in automotive industry and is of great importance. Besides cutting the costs, predictive maintenance can improve feeling of comfort and safety, by early detection, isolation and prediction of prospective failures. That is why automotive industry and fleet managers are turning to predictive analytics to maintain a lead position in industry. In order to predict and mitigate components failure in advance, measurements data from vehicle parts are collected from sensory system mounted on vehicle parts, and employed to evaluate the health condition of the components. An unsupervised learning solution is proposed, in this work, for automatic processing, diagnosis and isolation of faults. This solution is used for advanced analytics of the collected time-series data in the back-end (assuming that faults were reported based on spectral analysis). A literature study on maintenance types with emphasis on predictive maintenance with application to chassis failure is done. Chassis failures and conventional failure detection techniques are also covered in this study. A data acquisition was done at Hällared test track and labelled data regarding error states of interest were collected. Performance of the proposed method was validated by automatics clustering of two error states, i.e. low tyre pressure and faulty wheel hub.
The Impact of MSI Phenotype by MLH1 Expression in Gastric Adenocarcinomas: Critical Analysis of the Brazilian Experience

BACKGROUND: Gastric cancer remains a clinical concern due to its high prevalence and mortality; consequently, efforts for comprehensive molecular subtyping, as related to morphology and prognosis, are mandatory. MATERIALS AND METHODS: We correlated the immunohistochemical expression profile of a panel with two major mismatch-repair (MMR) enzymes MLH1 and MSH2 with clinicopathological features and prognosis in a series of 133 gastric cancers and compared with worldwide experience. RESULTS: MMR negativity was found associated to clinicopathological features as proximal location, predominantly polypoid and fungating macroscopic types (Bormann´s type I and II), intestinal and tubular morphology according to Lauren´s and WHO systems respectively, expansible type according to Ming classification, heavy lymphoplasmacytic infiltrate and absent perineural infiltration. Loss of MLH1 immunoexpression was related to a beneficial impact on disease-specific survival; an independent prognostic impact at multivariate models was observed in cases with the loss of MLH1. CONCLUSIONS: Taken together, these results validate the biological significance of immunohistochemical detection of MMR enzymes as a method to identify specific pathological features and to assess prognosis in gastric cancer.
Binary Phase Shift Keying Simulation with MATLAB and SIMULINK

Digital Communication follows one fundamental concept and it is the transfer of information from one point to another over an analog channel. In our modern society there is one method which is versatile and widely used in transferring digital data and this method is called Digital Phase Modulation. In Digital Phase Modulation it is possible to use discrete values in the carrier frequency or amplitude in order to represent their values in ones and zeros. Given this possibility, it can be concluded that it is also possible to represent digital data using phase. Such technique is called Phase Shift Keying. The easiest approach to Phase Shift Keying is the Binary Phase Shift keying or BPSK. In Binary Phase Shift Keying, hinted from the keyword binary, it uses only two phases with each used for logic high and logic low which can be represented with a minimum and maximum value of 0 degrees for logic low and 180 degrees for logic high. This Modulation Technique utilizes a balance modulator which consists of a carrier sine wave and a binary sequence which is to be used as input in order to generate the Phase Shift Keying Output desired.