Mining Scientific Articles Powered by Machine Learning Techniques

Literature review is one of the most important phases of research. Scientists must identify the gaps and challenges about certain area and the scientific literature, as a result of the accumulation of knowledge, should provide enough information. The problem is where to find the best and most important articles that guarantees to ascertain the state of the art on that specific domain. A feasible literature review consists on locating, appraising, and synthesising the best empirical evidences in the pool of available publications, guided by one or more research questions. Nevertheless, it is not assured that searching interesting articles in electronic databases will retrieve the most relevant content. Indeed, the existent search engines try to recommend articles by only looking for the occurrences of given keywords. In fact, the relevance of a paper should depend on many other factors as adequacy to the theme, specific tools used or even the test strategy, making automatic recommendation of articles a challenging problem. Our approach allows researchers to browse huge article collections and quickly find the appropriate publications of particular interest by using machine learning techniques. The proposed solution automatically classifies and prioritises the relevance of scientific papers. Using previous samples manually classified by domain experts, we apply a Naive Bayes Classifier to get predicted articles from real world journal repositories such as IEEE Xplore or ACM Digital. Results suggest that our model can substantially recommend, classify and rank the most relevant articles of a particular scientific field of interest. In our experiments, we achieved 98.22% of accuracy in recommending articles that are present in an expert classification list, indicating a good prediction of relevance. The recommended papers worth, at least, the reading. We envisage to expand our model in order to accept user's filters and other inputs to improve predictions.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Departamento de Engenharia Informática Faculdade of Engenharia Universidade do PortoPIXEL Research Group UNEMATLIACC - Artificial Intelligence and Computing Science Laboratory Universidade do PortoLIAADDepartamento de Computação Faculdade de Ciências Universidade Estadual PaulistaDepartamento de Computação Faculdade de Ciências Universidade Estadual PaulistaCAPES: BEX 1338/14-

A mediation approach to understanding socio-economic inequalities in maternal health-seeking behaviours in Egypt.

BACKGROUND: The levels and origins of socio-economic inequalities in health-seeking behaviours in Egypt are poorly understood. This paper assesses the levels of health-seeking behaviours related to maternal care (antenatal care [ANC] and facility delivery) and their accumulation during pregnancy and childbirth. Secondly, it explores the mechanisms underlying the association between socio-economic position (SEP) and maternal health-seeking behaviours. Thirdly, it examines the effectiveness of targeting of free public ANC and delivery care. METHODS: Data from the 2008 Demographic and Health Survey were used to capture two latent constructs of SEP: individual socio-cultural capital and household-level economic capital. These variables were entered into an adjusted mediation model, predicting twelve dimensions of maternal health-seeking; including any ANC, private ANC, first ANC visit in first trimester, regular ANC (four or more visits during pregnancy), facility delivery, and private delivery. ANC and delivery care costs were examined separately by provider type (public or private). RESULTS: While 74.2% of women with a birth in the 5-year recall period obtained any ANC and 72.4% delivered in a facility, only 48.8% obtained the complete maternal care package (timely and regular facility-based ANC as well as facility delivery) for their most recent live birth. Both socio-cultural capital and economic capital were independently positively associated with receiving any ANC and delivering in a facility. The strongest direct effect of socio-cultural capital was seen in models predicting private provider use of both ANC and delivery. Despite substantial proportions of women using public providers reporting receipt of free care (ANC: 38%, delivery: 24%), this free-of-charge public care was not effectively targeted to women with lowest economic resources. CONCLUSIONS: Socio-cultural capital is the primary mechanism leading to inequalities in maternal health-seeking in Egypt. Future studies should therefore examine the objective and perceived quality of care from different types of providers. Improvements in the targeting of free public care could help reduce the existing SEP-based inequalities in maternal care coverage in the short term

Tumor innate immunity primed by specific interferon-stimulated endogenous retroviruses.

Mesenchymal tumor subpopulations secrete pro-tumorigenic cytokines and promote treatment resistance1-4. This phenomenon has been implicated in chemorefractory small cell lung cancer and resistance to targeted therapies5-8, but remains incompletely defined. Here, we identify a subclass of endogenous retroviruses (ERVs) that engages innate immune signaling in these cells. Stimulated 3 prime antisense retroviral coding sequences (SPARCS) are oriented inversely in 3' untranslated regions of specific genes enriched for regulation by STAT1 and EZH2. Derepression of these loci results in double-stranded RNA generation following IFN-γ exposure due to bi-directional transcription from the STAT1-activated gene promoter and the 5' long terminal repeat of the antisense ERV. Engagement of MAVS and STING activates downstream TBK1, IRF3, and STAT1 signaling, sustaining a positive feedback loop. SPARCS induction in human tumors is tightly associated with major histocompatibility complex class 1 expression, mesenchymal markers, and downregulation of chromatin modifying enzymes, including EZH2. Analysis of cell lines with high inducible SPARCS expression reveals strong association with an AXL/MET-positive mesenchymal cell state. While SPARCS-high tumors are immune infiltrated, they also exhibit multiple features of an immune-suppressed microenviroment. Together, these data unveil a subclass of ERVs whose derepression triggers pathologic innate immune signaling in cancer, with important implications for cancer immunotherapy

Genome-wide association study for type 2 diabetes in Indians identifies a new susceptibility locus at 2q21

Meta-AnalysisThis is the final version of the article. Available from the American Diabetes Association via the DOI in this record.Indians undergoing socioeconomic and lifestyle transitions will be maximally affected by epidemic of type 2 diabetes (T2D). We conducted a two-stage genome-wide association study of T2D in 12,535 Indians, a less explored but high-risk group. We identified a new type 2 diabetes-associated locus at 2q21, with the lead signal being rs6723108 (odds ratio 1.31; P = 3.32 × 10⁻⁹). Imputation analysis refined the signal to rs998451 (odds ratio 1.56; P = 6.3 × 10⁻¹²) within TMEM163 that encodes a probable vesicular transporter in nerve terminals. TMEM163 variants also showed association with decreased fasting plasma insulin and homeostatic model assessment of insulin resistance, indicating a plausible effect through impaired insulin secretion. The 2q21 region also harbors RAB3GAP1 and ACMSD; those are involved in neurologic disorders. Forty-nine of 56 previously reported signals showed consistency in direction with similar effect sizes in Indians and previous studies, and 25 of them were also associated (P < 0.05). Known loci and the newly identified 2q21 locus altogether explained 7.65% variance in the risk of T2D in Indians. Our study suggests that common susceptibility variants for T2D are largely the same across populations, but also reveals a population-specific locus and provides further insights into genetic architecture and etiology of T2D.The major funding for this work comes from Council for Scientific and Industrial Research, Government of India, in the form of the grant “Diabetes mellitus—New drug discovery R&D, molecular mechanisms, and genetic and epidemiological factors” (NWP0032-19). R.T. received a postdoctoral fellowship from the Fogarty International Center and the Eunice Kennedy Shriver National Institute of Child Health and Human Development at the National Institutes of Health (D43-HD-065249)

Diabetic nephropathy and its risk factors among patients with diabetes mellitus-an observational study

Background: Diabetic nephropathy (DN) is frequently associated with T2DM and the leading cause of chronic kidney disease and end-stage renal disease. Diabetic nephropathy is one of the three classic micro-vascular complications of diabetes mellitus (DM), traditionally described among patients with long duration and poor control of DM. The aim of this study was to identify and evaluate the risk factors for diabetic nephropathy among patients with DM. Methods: This was a retrospective observational study and was conducted in the department of medicine, LABAID specialized hospital, Dhaka, Bangladesh during the period from March 2022 to March 2023. We included 345 patients with DM and diabetic nephropathy in our study. Results: In our study the mean age was 43.1±9.3 years and majority (57%) of patients were female. Among all patients 48% had diabetes for less than 8 years. Majority (72%) patients got nephropathy because of elevated glucose levels. We found other risk factors like advanced age (37.39%), smoking (27.83%), obesity (61.16%), elevated blood pressure (53.33%), dyslipidemia (20%), longer duration of diabetes (47.25%), family history of DM and DN (21.45% and 24.35%) and retinopathy (25.80%). Conclusions: In our study, we found advanced age, high glucose level, high blood pressure, obesity, long duration of DM, family history of DM and diabetic nephropathy, smoking, dyslipidemia and concomitant diabetic retinopathy were significant risk factors for diabetic nephropathy among selected diagnosed diabetic patients

A rare case of mucinous cystedenoma in adoloscence

Mucinous cystadenomas are one of the rarely found benign ovarian neoplasms seen in adolescents. They are commonly known for their massive size causing compressive effects ranging from pressure, pain, bloating, and urinary symptoms. As time passes by, these adnexal masses can lead to severe and fatal complications, such as ovarian torsion or haemorrhage. Accidental findings of these tumours are common as many of these patients are usually asymptomatic. Pelvic examinations and imaging studies can be used to further diagnose symptomatic patients and aid physicians in developing an appropriate course of treatment. A case of 18-year-old unmarried nulligravida presented with abdominal distension and mass per abdomen for the past 4 months, clinical examination revealed a mass of 32-34 weeks size, cystic in consistency, lower mass was not palpable, ultrasonography and magnetic resonance imaging (MRI) of abdomen and pelvis showed a large abdominopelvic multiloculated thin-walled lesion of size 17×21×30 with thin walled septations with enhancing intensity likely arising from the right adnexa. Mucinous cystadenoma patient was operated, staging laparotomy was done showed a huge large right ovarian cyst 26×15×9 cm, with no abnormalities noted in the uterus, appendix and left ovary. The histopathology report showed as mucinous cystadenoma. The patient was surgically managed by exploratory laparotomy with right ovarian salpingoophorectomy was done, patient was discharged in stable condition and advised follow-up in gynaecology OPD. Incidence of mucinous cystadenoma is very rare in adolescents. Here we report a case of mucinous cystadenoma, detailing the clinical presentation, diagnosis, pathologic review, imaging findings and management.

Survey on data aggregation based security attacks in wireless sensor network

Wireless sensor network (WSN) has applications in military, health care, environmental monitoring, infrastructure, industrial and commercial applications. The WSN is expected to maintain data integrity in all its network operations. However, due to the nature of wireless connectivity, WSN is prone to various attacks that alter or steal the data exchanged between the nodes. These attacks can disrupt the network processes and also the accuracy of its results. In this survey paper, we have reviewed various attacks available in the literature till date. We have also listed existing methods that focus on data aggregation based security mechanisms in WSN to counter the attacks. We have classified and compared these methods owing to their encryption techniques. This paper intends to support researchers to understand the basic attacks prevalent in WSN and schemes to counter such attacks

Comparative node selection-based localization technique for wireless sensor networks: A bilateration approach

Wireless sensor networks find extensive applications, such as environmental and smart city monitoring, structural health, and target location. To be useful, most sensor data must be localized. We propose a node localization technique based on bilateration comparison (BACL) for dense networks, which considers two reference nodes to determine the unknown position of a third node. The mirror positions resulted from bilateration are resolved by comparing their coordinates with the coordinates of the reference nodes. Additionally, we use network clustering to further refine the location of the nodes. We show that BACL has several advantages over Energy Aware Co-operative Localization (EACL) and Underwater Recursive Position Estimation (URPE): (1) BACL uses bilateration (needs only two reference nodes) instead of trilateration (that needs three reference nodes), (2) BACL needs reference (anchor) nodes only on the field periphery, and (3) BACL needs substantially less communication and computation. Through simulation, we show that BACL localization accuracy, as root mean square error, improves by 53% that of URPE and by 40% that of EACL. We also explore the BACL localization error when the anchor nodes are placed on one or multiple sides of a rectangular field, as a trade-off between localization accuracy and network deployment effort. Best accuracy is achieved using anchors on all field sides, but we show that localization refinement using node clustering and anchor nodes only on one side of the field has comparable localization accuracy with anchor nodes on two sides but without clustering

Tumour Cell Heterogeneity.

The population of cells that make up a cancer are manifestly heterogeneous at the genetic, epigenetic, and phenotypic levels. In this mini-review, we summarise the extent of intra-tumour heterogeneity (ITH) across human malignancies, review the mechanisms that are responsible for generating and maintaining ITH, and discuss the ramifications and opportunities that ITH presents for cancer prognostication and treatment