Towards a Mobile Malware Detection Framework with the Support of Machine Learning

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Serum ferritin levels, socio-demographic factors and desferrioxamine therapy in multi-transfused thalassemia major patients at a government tertiary care hospital of Karachi, Pakistan

<p>Abstract</p> <p>Background</p> <p>Beta thalassemia is the most frequent genetic disorder of haemoglobin synthesis in Pakistan. Recurrent transfusions lead to iron-overload manifested by increased serum Ferritin levels, for which chelation therapy is required.</p> <p>Findings</p> <p>The study was conducted in the Pediatric Emergency unit of Civil Hospital Karachi after ethical approval by the Institutional Review Board of Dow University of Health Sciences. Seventy nine cases of beta thalassemia major were included after a written consent. The care takers were interviewed for the socio-demographic variables and the use of Desferrioxamine therapy, after which a blood sample was drawn to assess the serum Ferritin level. SPSS 15.0 was employed for data entry and analysis.</p> <p>Of the seventy-nine patients included in the study, 46 (58.2%) were males while 33 (41.8%) were females. The mean age was 10.8 (± 4.5) years with the dominant age group (46.2%) being 10 to 14 years. In 62 (78.8%) cases, the care taker education was below the tenth grade. The mean serum Ferritin level in our study were 4236.5 ng/ml and showed a directly proportional relationship with age. Desferrioxamine was used by patients in 46 (58.2%) cases with monthly house hold income significant factor to the use of therapy.</p> <p>Conclusions</p> <p>The mean serum Ferritin levels are approximately ten times higher than the normal recommended levels for normal individuals, with two-fifths of the patients not receiving iron chelation therapy at all. Use of iron chelation therapy and titrating the dose according to the need can significantly lower the iron load reducing the risk of iron-overload related complications leading to a better quality of life and improving survival in Pakistani beta thalassemia major patients.</p> <p>Conflicts of Interest: None</p

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Evaluation of Tree Based Machine Learning Classifiers for Android Malware Detection

Android is a most popular mobile-based operating system with billions of active users, which has encouraged hackers and cyber-criminals to push the malware into this operating system. Accordingly, extensive research has been conducted on malware analysis and detection for Android in recent years; and Android has developed and implemented numerous security controls to deal with the problems, including unique ID (UID) for each application, system permissions, and its distribution platform Google Play. In this paper, we evaluate four tree-based machine learning algorithms for detecting Android malware in conjunction with a substring-based feature selection method for the classifiers. In the experiments 11,120 apps of the DREBIN dataset were used where 5,560 contain malware samples and the rest are benign. It is found that the Random Forest classifier outperforms the best previously reported result (around 94% accuracy, obtained by SVM) with 97.24% accuracy, and thus provides a strong basis for building effective tools for Android malware detection

Dealing with Class Imbalance in Android Malware Detection by Cascading Clustering and Classification

The high&nbsp;number of Android devices that are active around the world makes these platforms appealing targets for malware attacks. A malware is shorthand for malicious applications developed by cyber attackers with the intention of gaining access or causing damage to a computer device or network, often while the victim remains oblivious to the fact there’s been a compromise. Android security requires machine learning approaches to quickly and accurately flag malicious applications. This paper describes a supervised learning approach for classifying Android applications as genuine or malicious. It uses reverse engineering to look for dangerous capabilities within the application code and structure before it is executed and applies to an intriguing combination of clustering and classification, in order to deal with the imbalanced data problem and avoid a detection system that skews towards modeling the genuine applications. We use benchmark Android applications to assess that the presented approach is able to correctly detect malware applications. The significance of the computed detection patterns is evaluated using established machine learning metrics

Regulation of G₂/M cell cycle DNA damage checkpoints

Deregulation of the cell cycle checkpoints is a key step in tumorigenesis. we present evidence that apart from CDC25, WEE1 may also be important for the G₂/M DNA damage checkpoints. ING1 is a candidate tumor suppressor that cooperates with p53 to inhibit cell proliferation. We show that ING1 can regulate the cell cycle and the DNA damage responses at G₂/M phase independent of p53 functions. ING1b enhanced the p53-independent G₂/M DNA damage checkpoint induced by adriamycin, but did not affect the G₁ DNA damage checkpoint. No significant transactivation of p21^CIP1/WAF1 and MDM2 by ING1 in the absence of p53 was observed, suggesting that mechanisms involving activation of p53-related proteins are unlikely to contribute to the G₂/M cell cycle arrest caused by ING1b. These data provide evidence of the involvement of WEE1 and ING1 in the G₂/M DNA damage checkpoint. Understanding precisely how these proteins regulate the cell cycle and checkpoints may shed light on the mechanism of tumorigenesis